Scientific Work Using or Referencing ELKI

Over the years, ELKI has been increasingly cited/used in scientific publications and other software projects.

The following list is automatically generated from very heterogenous sources, and may contain errors. Where possible, we try to use metadata from DBLP, CrossRef.org, OpenCitations, SemanticScholar, Microsoft Academic Search, and HTML meta headers from the publisher web pages. For theses, seminar articles etc. this approach does however not work. We have not verified every citation discovered by the bot.

2024

  1. Francisco V. Cipolla Ficarra (2024). Machine Learning and Human Unlearning. Extended Selected Papers of the 14th International Conference on Information, Intelligence, Systems, and Applications, 72-118, Springer Nature Switzerland, 10.1007/978-3-031-67426-6_4
  2. Philipp Röchner, Henrique O. Marques, Ricardo J. G. B. Campello, and Arthur Zimek (2024). Evaluating outlier probabilities: assessing sharpness, refinement, and calibration using stratified and weighted measures. Data Mining and Knowledge Discovery, Springer Science and Business Media LLC, 10.1007/s10618-024-01056-5
  3. Kenneth S. Berenhaut, John D. Foley, and Liangdongsheng Lyu (2024). Generalized Partitioned Local Depth. Journal of Statistical Theory and Practice 18(1), Springer Science and Business Media LLC, 10.1007/s42519-023-00356-1
  4. Guoxian Yu, Liangrui Ren, Jun Wang, Carlotta Domeniconi, and Xiangliang Zhang (2024). Multiple clusterings: Recent advances and perspectives. Comput. Sci. Rev. 52, 100621, 10.1016/j.cosrev.2024.100621, BibTeX
  5. Eduardo Luis Gomes, Mauro Sérgio Pereira Fonseca, André Eugênio Lazzaretti, Anelise Munaretto, and Carlos Rafael Guerber (2024). Sliding Window, Hierarchical Classification, Regression, and Genetic Algorithm for RFID Indoor Positioning Systems. Expert Syst. Appl. 238(Part E), 122298, 10.1016/j.eswa.2023.122298, BibTeX
  6. Haoyu Wang, Changqing Song, Jinfeng Wang, and Peichao Gao (2024). A raster-based spatial clustering method with robustness to spatial outliers. Scientific Reports 14(1), Springer Science and Business Media LLC, 10.1038/s41598-024-53066-4
  7. Klaudyna Borewicz, Bastian Hornung, Fangjie Gu, Pieter H. van der Zaal, Henk A. Schols, Peter J. Schaap, and Hauke Smidt (2024). Metatranscriptomic analysis indicates prebiotic effect of isomalto/malto-polysaccharides on human colonic microbiota in-vitro. Scientific Reports 14(1), Springer Science and Business Media LLC, 10.1038/s41598-024-69685-w
  8. Ahmet Çinar, F. Sibel Salman, Ozgur M. Araz, and Mert Parcaoglu (2024). Managing Home Health-Care Services With Dynamic Arrivals During a Public Health Emergency. IEEE Trans. Engineering Management 71, 13312-13326, 10.1109/TEM.2022.3209962, BibTeX
  9. Woojin Doo, and Heeyoung Kim (2024). Simultaneous Deep Clustering and Feature Selection via K-Concrete Autoencoder. IEEE Trans. Knowl. Data Eng. 36(6), 2629-2642, 10.1109/TKDE.2023.3323580, BibTeX
  10. Youwei Liang, Dong Huang, Chang-Dong Wang, and Philip S. Yu (2024). Multi-View Graph Learning by Joint Modeling of Consistency and Inconsistency. IEEE Trans. Neural Networks Learn. Syst. 35(2), 2848-2862, 10.1109/TNNLS.2022.3192445, BibTeX
  11. Linlin Zong, Faqiang Miao, Xianchao Zhang, Wenxin Liang, and Bo Xu (2024). Self-Supervised Deep Multiview Spectral Clustering. IEEE Trans. Neural Networks Learn. Syst. 35(3), 4299-4308, 10.1109/TNNLS.2022.3195780, BibTeX
  12. Shudong Huang, Ivor W. Tsang, Zenglin Xu, and Jiancheng Lv (2024). CGDD: Multiview Graph Clustering via Cross-Graph Diversity Detection. IEEE Trans. Neural Networks Learn. Syst. 35(3), 4206-4219, 10.1109/TNNLS.2022.3201964, BibTeX
  13. Chunbo Liu, Liyin Wang, Zhikai Zhang, Chunmiao Xiang, Zhaojun Gu, Zhi Wang, and Shuang Wang (2024). Unsupervised Intrusion Detection Based on Asymmetric Auto-Encoder Feature Extraction. IEICE Trans. Inf. Syst. 107(9), 1161-1173, 10.1587/transinf.2024edp7001, BibTeX
  14. Wenke Li, and Zhou Zhou (2024). A Data Generator for Benchmark Evaluation of Clustering Algorithms. Elsevier BV, 10.2139/ssrn.4706048
  15. Zeyi Li, Pan Wang, and Zixuan Wang (2024). FlowGANAnomaly: Flow-Based Anomaly Network Intrusion Detection with Adversarial Learning. Chinese Journal of Electronics 33(1), 58-71, IEEE, 10.23919/cje.2022.00.173
  16. Niharika Sharma, Bhavna Arora, Shabana Ziyad, Pradeep Kumar Singh, and Yashwant Singh (2024). A Holistic review and performance evaluation of unsupervised learning methods for network anomaly detection. International Journal on Smart Sensing and Intelligent Systems 17(1), Walter de Gruyter GmbH, 10.2478/ijssis-2024-0016
  17. Sunil Aryal, Jonathan R. Wells, Arbind Agrahari Baniya, and KC Santosh (2024). Enabling clustering algorithms to detect clusters of varying densities through scale-invariant data preprocessing. CoRR abs/2401.11402, 10.48550/arXiv.2401.11402, BibTeX
  18. Maohan Liang, Ryan Wen Liu, Ruobin Gao, Zhe Xiao, Xiaocai Zhang, and Hua Wang (2024). A Survey of Distance-Based Vessel Trajectory Clustering: Data Pre-processing, Methodologies, Applications, and Experimental Evaluation. CoRR abs/2407.11084, 10.48550/arXiv.2407.11084, BibTeX

2023

  1. Marcos Lordello Chaim, Kesina Baral, Jeff Offutt, Mario Concilio Neto, and Roberto Paulo Andrioli de Araujo (2023). On subsumption relationships in data flow testing. Softw. Test. Verification Reliab. 33(6), 10.1002/stvr.1843, BibTeX
  2. Maelle Moranges, Marc Plantevit, and Moustafa Bensafi (2023). Peripheral Nervous System Responses to Food Stimuli: Analysis Using Data Science Approaches. Basic Protocols on Emotions, Senses, and Foods, 233-246, Springer US, 10.1007/978-1-0716-2934-5_18
  3. Tomasz Walkowiak, Kamil Szyc, and Henryk Maciejewski (2023). Combining Outlierness Scores and Feature Extraction Techniques for Improvement of OoD and Adversarial Attacks Detection in DNNs. ICCS (1), 578-592, Springer, 10.1007/978-3-031-35995-8_41, BibTeX
  4. Andreas Lang, and Erich Schubert (2023). Accelerating k-Means Clustering with Cover Trees. SISAP, 148-162, Springer, 10.1007/978-3-031-46994-7_13, BibTeX
  5. Alexander Hartl, Félix Iglesias, and Tanja Zseby (2023). dSalmon: High-Speed Anomaly Detection for Evolving Multivariate Data Streams. VALUETOOLS, 153-169, Springer, 10.1007/978-3-031-48885-6_10, BibTeX
  6. Shiyuan Fu, Xin Gao, Baofeng Li, Bing Xue, Xin Jia, Zijian Huang, Guangyao Zhang, and Xu Huang (2023). Two Outlier-Sensitive Measures for Semi-supervised Dynamic Ensemble Anomaly Detection Models. Neural Process. Lett. 55(3), 3429-3470, 10.1007/s11063-022-11017-y, BibTeX
  7. Hafiz Qasim Ali, Aryan Kheyabani, Cagdas Akalın, Adnan Kefal, and Mehmet Yildiz (2023). Numerical and experimental methodologies to investigate the damage progression inside the axisymmetric composite cylinders with cutouts under torsion. Composite Structures 315, 116990, Elsevier BV, 10.1016/j.compstruct.2023.116990
  8. Xian Yu, Siqian Shen, Babak Badri-Koohi, and Haitham Seada (2023). Time window optimization for attended home service delivery under multiple sources of uncertainties. Comput. Oper. Res. 150, 106045, 10.1016/j.cor.2022.106045, BibTeX
  9. Piotr A. Kowalski, Maciej Kusy, and Karol Kocierz (2023). The forensic information identification based on machine learning algorithms. Forensic Sci. Int. Digit. Investig. 47, 301619, 10.1016/j.fsidi.2023.301619, BibTeX
  10. Christian Emeka Okafor, Sunday Iweriolor, Okwuchukwu Innocent Ani, Shahnawaz Ahmad, Shabana Mehfuz, Godspower Onyekachukwu Ekwueme, Okechukwu Emmanuel Chukwumuanya, Sylvester Emeka Abonyi, Ignatius Echezona Ekengwu, and Okechukwu Peter Chikelu (2023). Advances in machine learning-aided design of reinforced polymer composite and hybrid material systems. Hybrid Advances 2, 100026, Elsevier BV, 10.1016/j.hybadv.2023.100026
  11. Zihan Fang, Shide Du, Xincan Lin, Jinbin Yang, Shiping Wang, and Yiqing Shi (2023). DBO-Net: Differentiable bi-level optimization network for multi-view clustering. Inf. Sci. 626, 572-585, 10.1016/j.ins.2023.01.071, BibTeX
  12. Renjie Lin, Yongkun Lin, Zhenghong Lin, Shide Du, and Shiping Wang (2023). CCR-Net: Consistent contrastive representation network for multi-view clustering. Inf. Sci. 637, 118937, 10.1016/j.ins.2023.118937, BibTeX
  13. Nuno Fachada, and Diogo de Andrade (2023). Generating multidimensional clusters with support lines. Knowl. Based Syst. 277, 110836, 10.1016/j.knosys.2023.110836, BibTeX
  14. Haonan Huang, Guoxu Zhou, Yanghang Zheng, Zuyuan Yang, and Qibin Zhao (2023). Exclusivity and consistency induced NMF for multi-view representation learning. Knowl. Based Syst. 281, 111020, 10.1016/j.knosys.2023.111020, BibTeX
  15. Liting Huang, Xiangyang Fan, Tianlin Xia, Yuhang Li, and Youdong Ding (2023). SC2-Net: Self-supervised learning for multi-view complementarity representation and consistency fusion network. Neurocomputing 556, 126695, 10.1016/j.neucom.2023.126695, BibTeX
  16. Yuhong Chen, Zhihao Wu, Zhaoliang Chen, Mianxiong Dong, and Shiping Wang (2023). Joint learning of feature and topology for multi-view graph convolutional network. Neural Networks 168, 161-170, 10.1016/j.neunet.2023.09.006, BibTeX
  17. Jian Hou, Huaqiang Yuan, and Marcello Pelillo (2023). Towards Parameter-Free Clustering for Real-World Data. Pattern Recognit. 134, 109062, 10.1016/j.patcog.2022.109062, BibTeX
  18. Gargi Mishra, and Rajeev Kumar (2023). An individual fairness based outlier detection ensemble. Pattern Recognit. Lett. 171, 76-83, 10.1016/j.patrec.2023.05.010, BibTeX
  19. Nguyen Van Thieu, Diego Oliva, and Marco Pérez-Cisneros (2023). MetaCluster: An open-source Python library for metaheuristic-based clustering problems. SoftwareX 24, 101597, 10.1016/j.softx.2023.101597, BibTeX
  20. Yijun Zhang, Han Bao, Lingsen Meng, and Yosuke Aoki (2023). Understanding and Mitigating the Spatial Bias of Earthquake Source Imaging With Regional Slowness Enhanced Back‐Projection. Journal of Geophysical Research: Solid Earth 128(5), American Geophysical Union (AGU), 10.1029/2022JB025525
  21. Yisen Lin, Ye Wang, Huichen Qu, and Yiwen Xiong (2023). Research on stress curve clustering algorithm of Fiber Bragg grating sensor. Scientific Reports 13(1), Springer Science and Business Media LLC, 10.1038/s41598-023-39058-w
  22. Zheng Zuo, Ziqiang Li, Pengsen Cheng, and Jian Zhao (2023). A novel subspace outlier detection method by entropy-based clustering algorithm. Scientific Reports 13(1), Springer Science and Business Media LLC, 10.1038/s41598-023-42261-4
  23. Furkan Gözükara, and Selma Ayse Özel (2023). An Incremental Hierarchical Clustering Based System For Record Linkage In E-Commerce Domain. Comput. J. 66(3), 581-602, 10.1093/COMJNL/BXAB179, BibTeX
  24. Patrick Eiring, Teresa Klein, Simone Backes, Marcel Streit, Sören Doose, Gerti Beliu, and Markus Sauer (2023). Coronaviruses use ACE2 monomers as entry receptors. Cold Spring Harbor Laboratory, 10.1101/2023.01.25.525479
  25. Naiyao Liang, Zuyuan Yang, and Shengli Xie (2023). Incomplete Multi-View Clustering With Sample-Level Auto-Weighted Graph Fusion. IEEE Trans. Knowl. Data Eng. 35(6), 6504-6511, 10.1109/TKDE.2022.3171911, BibTeX
  26. Guosheng Cui, Ruxin Wang, Dan Wu, and Ye Li (2023). Incomplete Multiview Clustering Using Normalizing Alignment Strategy With Graph Regularization. IEEE Trans. Knowl. Data Eng. 35(8), 8126-8142, 10.1109/TKDE.2022.3202561, BibTeX
  27. Lele Fu, Zhaoliang Chen, Yongyong Chen, and Shiping Wang (2023). Unified Low-Rank Tensor Learning and Spectral Embedding for Multi-View Subspace Clustering. IEEE Trans. Multim. 25, 4972-4985, 10.1109/TMM.2022.3185886, BibTeX
  28. Bao-Yu Liu, Ling Huang, Chang-Dong Wang, Jian-Huang Lai, and Philip S. Yu (2023). Multiview Clustering via Proximity Learning in Latent Representation Space. IEEE Trans. Neural Networks Learn. Syst. 34(2), 973-986, 10.1109/TNNLS.2021.3104846, BibTeX
  29. Huawen Liu, Xiaodan Xu, Enhui Li, Shichao Zhang, and Xuelong Li (2023). Anomaly Detection With Representative Neighbors. IEEE Trans. Neural Networks Learn. Syst. 34(6), 2831-2841, 10.1109/TNNLS.2021.3109898, BibTeX
  30. Haoli Zhao, Zhenni Li, Wuhui Chen, Zibin Zheng, and Shengli Xie (2023). Accelerated Partially Shared Dictionary Learning With Differentiable Scale-Invariant Sparsity for Multi-View Clustering. IEEE Trans. Neural Networks Learn. Syst. 34(11), 8825-8839, 10.1109/TNNLS.2022.3153310, BibTeX
  31. Guowang Du, Lihua Zhou, Kevin Lü, Hao Wu, and Zhimin Xu (2023). Multiview Subspace Clustering With Multilevel Representations and Adversarial Regularization. IEEE Trans. Neural Networks Learn. Syst. 34(12), 10279-10293, 10.1109/TNNLS.2022.3165542, BibTeX
  32. Sanjay Kumar Anand, and Suresh Kumar (2023). Experimental Comparisons of Clustering Approaches for Data Representation. ACM Comput. Surv. 55(3), 45:1-45:33, 10.1145/3490384, BibTeX
  33. Binglei Lou, David Boland, and Philip H. W. Leong (2023). fSEAD: A Composable FPGA-based Streaming Ensemble Anomaly Detection Library. ACM Trans. Reconfigurable Technol. Syst. 16(3), 42:1-42:27, 10.1145/3568992, BibTeX
  34. Lei Zhang, Lele Fu, Tong Wang, Chuan Chen, and Chuanfu Zhang (2023). Mutual Information-Driven Multi-View Clustering. CIKM, 3268-3277, ACM, 10.1145/3583780.3614986, BibTeX
  35. Xueying Ding, Nikita Seleznev, Senthil Kumar, C. Bayan Bruss, and Leman Akoglu (2023). From Detection to Action: a Human-in-the-loop Toolkit for Anomaly Reasoning and Management. ICAIF, 279-287, ACM, 10.1145/3604237.3626872, BibTeX
  36. Shengkun Zhu, Quanqing Xu, Jinshan Zeng, Sheng Wang, Yuan Sun, Zhifeng Yang, Chuanhui Yang, and Zhiyong Peng (2023). F3KM: Federated, Fair, and Fast k-means. Proc. ACM Manag. Data 1(4), 241:1-241:25, 10.1145/3626728, BibTeX
  37. Ahmad. K. Kayed, and Abdelhakeem M. B. Abdelrahman (2023). Semantic Similarity Based on Association Measurement. Intelligent Internet of Things for Smart Healthcare Systems, 133-149, CRC Press, 10.1201/9781003326182-9
  38. Martina Trognitz (2023). Evaluation of Tools for Clustering of Archaeological Data. Tübingen University Press, 10.15496/publikation-87761
  39. Amin Ganjali Khosrowshahi, Iman Aghayan, Mehmet Metin Kunt, and Abdoul-Ahad Choupani (2023). Detecting crash hotspots using grid and density-based spatial clustering. Proceedings of the Institution of Civil Engineers - Transport 176(4), 200-212, Emerald, 10.1680/jtran.20.00028
  40. Dan Iter, Reid Pryzant, Ruochen Xu, Shuohang Wang, Yang Liu, Yichong Xu, and Chenguang Zhu (2023). In-Context Demonstration Selection with Cross Entropy Difference. EMNLP (Findings), 1150-1162, Association for Computational Linguistics, 10.18653/v1/2023.findings-emnlp.81, BibTeX
  41. Dror Haor, Hagit Liven, Mira Barshai, Eitan Sela, Gordon R. Smith, and Yakir Preisler (2023). A Novel Carbon Stocking Estimation Through Continuous Catalog Learning. Springer Science and Business Media LLC, 10.21203/rs.3.rs-3472743/v1
  42. Viet-Vu Vu, Byeongnam Yoon, Dinh-Lam Pham, Hong-Quan Do, Hai-Minh Nguyen, Tran-Chung Dao, Thi-Hai-Yen Nguyen, Doan-Vinh Tran, Thi-Huong-Ly Nguyen, and Viet-Thang Vu (2023). Density peak clustering evaluation. ICACT, 126-129, IEEE, 10.23919/ICACT56868.2023.10079561, BibTeX
  43. Mbulelo S. P. Ngongoma, Musasa Kabeya, and Katleho Moloi (2023). A Review of Plant Disease Detection Systems for Farming Applications. Applied Sciences 13(10), 5982, Mdpi Ag, 10.3390/app13105982
  44. David Muhr, Michael Affenzeller, and Josef Küng (2023). A Probabilistic Transformation of Distance-Based Outliers. Mach. Learn. Knowl. Extr. 5(3), 782-802, 10.3390/make5030042, BibTeX
  45. Jun Zhao, Wenyu Rong, and Di Liu (2023). Urban Agglomeration High-Speed Railway Backbone Network Planning: A Case Study of Beijing-Tianjin-Hebei Region, China. Sustainability 15(8), 6450, Mdpi Ag, 10.3390/su15086450
  46. Jinyang Liu, Shilin He, Zhuangbin Chen, Liqun Li, Yu Kang, Xu Zhang, Pinjia He, Hongyu Zhang, Qingwei Lin, Zhangwei Xu, Saravan Rajmohan, Dongmei Zhang, and Michael R. Lyu (2023). Incident-aware Duplicate Ticket Aggregation for Cloud Systems. CoRR abs/2302.09520, 10.1109/icse48619.2023.00193, BibTeX
  47. Xueying Ding, Nikita Seleznev, Senthil Kumar, C. Bayan Bruss, and Leman Akoglu (2023). From Explanation to Action: An End-to-End Human-in-the-loop Framework for Anomaly Reasoning and Management. CoRR abs/2304.03368, 10.48550/arXiv.2304.03368, BibTeX
  48. Roel Bouman, Zaharah Bukhsh, and Tom Heskes (2023). Unsupervised anomaly detection algorithms on real-world data: how many do we need?. CoRR abs/2305.00735, 10.48550/arXiv.2305.00735, BibTeX
  49. Anastasis Kratsios, Ruiyang Hong, and Haitz Sáez de Ocáriz Borde (2023). Capacity Bounds for Hyperbolic Neural Network Representations of Latent Tree Structures. CoRR abs/2308.09250, 10.48550/arXiv.2308.09250, BibTeX
  50. Kingsley Ukoba, and Tien-Chien Jen (2023). Biochar and Application of Machine Learning: A Review. Biochar - Productive Technologies, Properties and Applications, IntechOpen, 10.5772/intechopen.108024
  51. Olga Chernovaa, Inna Mitrofanovab, Marina Pleshakovad, and Victoria Batmanovac (2023). Use of big data analytics for small and medium sized businesses. Serbian Journal of Management 18(1), 93-109, Centre for Evaluation in Education and Science (CEON/CEES), 10.5937/sjm18-41822
  52. Lars Lenssen, Niklas Strahmann, and Erich Schubert (2023). Fast k-Nearest-Neighbor-Consistent Clustering. LWDA, 387-398, CEUR-WS.org, BibTeX
  53. Maximilian Archimedes Xaver Hünemörder (2023). Advances in Unsupervised Learning and Applications: Background knowledge driven subspace clustering, semantic password guessing and learned index structures. University of Kiel, Germany, BibTeX
  54. Durgesh Srivastava, Neha Sharma, Deepak Sinwar, Jabar H. Yousif, and Hari Prabhat Gupta (2023). Intelligent Internet of Things for Smart Healthcare Systems. CRC Press, 9781000834970
  55. Erman Acar, Andrea De Domenico, Krishna Manoorkar, and Mattia Panettiere (2023). A Meta-Learning Algorithm for Interrogative Agendas. arXiv 2301.01837
  56. Steeven Janny, Aurélien Béneteau, Madiha Nadri, Julie Digne, Nicolas Thome, and Christian Wolf (2023). Eagle: Large-Scale Learning of Turbulent Fluid Dynamics with Mesh Transformers. arXiv 2302.10803
  57. Justin Sam Chew, and Maurice HT Ling (2023). TAPPS Release 1: Plugin-Extensible Platform for Technical Analysis and Applied Statistics. arXiv 2302.12056
  58. Alaeddine Zahir, Khalide Jbilou, and Ahmed Ratnani (2023). High-dimensional multi-view clustering methods. arXiv 2303.08582
  59. Yanhua Xu (2023). Machine Learning for Flow Cytometry Data Analysis. arXiv 2303.09007
  60. Michael J. Zellinger, and Peter Bühlmann (2023). High-Level Synthetic Data Generation with Data Set Archetypes. arXiv 2303.14301
  61. Jonas Soenen, Elia Van Wolputte, Vincent Vercruyssen, Wannes Meert, and Hendrik Blockeel (2023). AD-MERCS: Modeling Normality and Abnormality in Unsupervised Anomaly Detection. arXiv 2305.12958
  62. Xiangzhu Meng, Wei Wei, Qiang Liu, Shu Wu, and Liang Wang (2023). TCGF: A unified tensorized consensus graph framework for multi-view representation learning. arXiv 2309.09987
  63. Jan Mendling, Henrik Leopold, Henning Meyerhenke, and Benoît Depaire (2023). Methodology of Algorithm Engineering. arXiv 2310.18979
  64. Alaeddine Zahir, Khalide Jbilou, and Ahmed Ratnani (2023). A low-rank non-convex norm method for multiview graph clustering. arXiv 2312.11157
  65. Adem Demirtop, and Ali Hakan Işık (2023). Yapay Sinir Ağları ile Rüzgâr Enerji Verimliliğine Yönelik Yeni Bir Tahmin Yaklaşımı: Çanakkale ili Bozcaada Örneği. International Journal of Engineering Design and Technology 5(1-2), 25-32, Burdur Mehmet Akif Ersoy University
  66. Erik Mjaaland Skår (2023). Exploring Linked List-based Trajectory Traversal for Efficient Topological Queries in Spatial Data. NTNU
  67. F. Sabry (2023). Narrow Artificial Intelligence: Fundamentals and Applications. One Billion Knowledgeable
  68. Héctor Díaz Beltrán (2023). Python implementation of an unsupervised learning algorithm: leveraged affinity propagation (Implementación Python de un algoritmo de aprendizaje no supervisado: propagación de afinidades ligera). Universidad de Oviedo
  69. Leonardo Rodrigues Ribeiro (2023). MetaLProjection: uma abordagem para recomendação de algoritmos de redução de dimensionalidade utilizando meta-aprendizagem (MetaLProjection: an approach to recommending dimensionality reduction algorithms using meta-learning). Universidade Federal da Bahia
  70. Natalia Apetrii (2023). Cadrul Psihopedagogic Și Tehnologic Al Cursului “ Data Mining” (The psycho-pedagogical and technological framework of the course “Data Mining).
  71. Sh.S. Musayev, and M.A Abduazizov (2023). Methods And Means Of Intellectual Analysis Of Log Files In The Detection Of Anomalous States Of Computer Systems. Ilm-fan va ta’lim 1(1)

2022

  1. Franco M. Zanotto, Diana Zapata Dominguez, Elixabete Ayerbe, Iker Boyano, Christine Burmeister, Marc Duquesnoy, Marlene Eisentraeger, Jonathan Florez Montaño, Alfonso Gallo‐Bueno, Lukas Gold, Florian Hall, Nicolaj Kaden, Bernhard Muerkens, Laida Otaegui, Yvan Reynier, Simon Stier, Matthias Thomitzek, Artem Turetskyy, Nicolas Vallin, Jacob Wessel, Xukuan Xu, Jeyhun Abbasov, and Alejandro A. Franco (2022). Data Specifications for Battery Manufacturing Digitalization: Current Status, Challenges, and Opportunities. Batteries & Supercaps 5(9), Wiley, 10.1002/batt.202200224
  2. Aurora Esteban, Amelia Zafra, and Sebastián Ventura (2022). Data mining in predictive maintenance systems: A taxonomy and systematic review. WIREs Data Mining Knowl. Discov. 12(5), 10.1002/widm.1471, BibTeX
  3. Evgeniya Tsarkova (2022). Technical Diagnostics of Equipment Using Data Mining Technologies. Lecture Notes in Networks and Systems, 1613-1622, Springer, 10.1007/978-3-030-96380-4_178
  4. Anh T. Dang, Raneem Qaddoura, Ala’ M. Al-Zoubi, Hossam Faris, and Pedro A. Castillo (2022). EvoCC: An Open-Source Classification-Based Nature-Inspired Optimization Clustering Framework in Python. EvoApplications, 77-92, Springer, 10.1007/978-3-031-02462-7_6, BibTeX
  5. Benjamin Ertl, Matthias Schneider, Jörg Meyer, and Achim Streit (2022). A Novel Semi-supervised Clustering Algorithm: CoExDBSCAN. Knowledge Discovery, Knowledge Engineering and Knowledge Management, 1-21, Springer, 10.1007/978-3-031-14602-2_1
  6. Erich Schubert (2022). Automatic Indexing for Similarity Search in ELKI. SISAP, 205-213, Springer, 10.1007/978-3-031-17849-8_16, BibTeX
  7. Erik Thordsen, and Erich Schubert (2022). On Projections to Linear Subspaces. SISAP, 75-88, Springer, 10.1007/978-3-031-17849-8_7, BibTeX
  8. Andrea Della Monaca, Massimo Cafaro, Marco Pulimeno, and Italo Epicoco (2022). An Adaptive Clustering Approach for Distributed Outlier Detection in Data Streams. DCAI (1), 86-99, Springer, 10.1007/978-3-031-20859-1_10, BibTeX
  9. Sven Hertling, and Heiko Paulheim (2022). DBkWik++- Multi Source Matching of Knowledge Graphs. KGSWC, 1-15, Springer, 10.1007/978-3-031-21422-6_1, BibTeX
  10. Luiz Henrique dos Santos Fernandes, Kate Smith-Miles, and Ana Carolina Lorena (2022). Generating Diverse Clustering Datasets with Targeted Characteristics. BRACIS (1), 398-412, Springer, 10.1007/978-3-031-21686-2_28, BibTeX
  11. Pan Wang, Zeyi Li, Xiaokang Zhou, Chunhua Su, and Weizheng Wang (2022). FlowADGAN: Adversarial Learning for Deep Anomaly Network Intrusion Detection. STM, 156-174, Springer, 10.1007/978-3-031-29504-1_9, BibTeX
  12. Swaroop Chigurupati, K. Raja, and M. S. Babu (2022). An Extensive Survey on Outlier Prediction Using Mining and Learning Approaches. Lecture Notes on Data Engineering and Communications Technologies, 593-610, Springer, 10.1007/978-981-16-9605-3_40
  13. Franka Bause, Erich Schubert, and Nils M. Kriege (2022). EmbAssi: embedding assignment costs for similarity search in large graph databases. Data Min. Knowl. Discov. 36(5), 1728-1755, 10.1007/s10618-022-00850-3, BibTeX
  14. Adrian Englhardt, Holger Trittenbach, Daniel Kottke, Bernhard Sick, and Klemens Böhm (2022). Efficient SVDD sampling with approximation guarantees for the decision boundary. Mach. Learn. 111(4), 1349-1375, 10.1007/s10994-022-06149-0, BibTeX
  15. Chang-an Yuan, Yonghua Zhu, Zhi Zhong, Wei Zheng, and Xiaofeng Zhu (2022). Robust self-tuning multi-view clustering. World Wide Web 25(2), 489-512, 10.1007/s11280-021-00945-9, BibTeX
  16. Bahaeddin Turkoglu, Sait Ali Uymaz, and Ersin Kaya (2022). Clustering analysis through artificial algae algorithm. Int. J. Mach. Learn. Cybern. 13(4), 1179-1196, 10.1007/s13042-022-01518-6, BibTeX
  17. Durgesh Samariya, and Jiangang Ma (2022). A New Dimensionality-Unbiased Score for Efficient and Effective Outlying Aspect Mining. Data Sci. Eng. 7(2), 120-135, 10.1007/s41019-022-00185-5, BibTeX
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  67. Nora Gourmelon, Siming Bayer, Michael Mayle, Guy Bach, Christian Bebber, Christophe Munck, Christoph Sosna, and Andreas Maier (2021). Implications of Experiment Set-Ups for Residential Water End-Use Classification. Water 13(2), 236, Mdpi Ag, 10.3390/W13020236
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  76. Erich Schubert (2021). HACAM: Hierarchical Agglomerative Clustering Around Medoids - and its Limitations. LWDA, 191-204, CEUR-WS.org, BibTeX
  77. Frank Nussbaum, and Joachim Giesen (2021). Robust principal component analysis for generalized multi-view models. UAI, 686-695, AUAI Press, BibTeX
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  83. Francisco José García García (2021). Efficient Query Processing in Distributed Spatial Data Management Systems. Universidad de Almería
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2020

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  4. Piotr A. Kowalski, Szymon Łukasik, Małgorzata Charytanowicz, and Piotr Kulczycki (2020). Optimizing Clustering with Cuttlefish Algorithm. Information Technology, Systems Research, and Computational Physics, 34-43, Springer, 10.1007/978-3-030-18058-4_3
  5. J. H. Kamdar, J. Jeba Praba, and John J. Georrge (2020). Artificial Intelligence in Medical Diagnosis: Methods, Algorithms and Applications. Machine Learning with Health Care Perspective, 27-37, Springer, 10.1007/978-3-030-40850-3_2
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  72. Παναγιώτα Κωτσάκη (2020). Διαχείριση Δεδομένων στις πλατφόρμες ΚΝΙΜE & WEKA. Πανεπιστήμιο Δυτικής Αττικής, 10.26265/polynoe-7
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  75. Andre Kummerow, Cristian Monsalve, Christoph Brosinsky, Steffen Nicolai, and Dirk Westermann (2020). A Novel Framework for Synchrophasor Based Online Recognition and Efficient Post-Mortem Analysis of Disturbances in Power Systems. Applied Sciences 10(15), 5209, Mdpi Ag, 10.3390/APP10155209
  76. Christopher Brooke, and Ben Clutterbuck (2020). Mapping Heterogeneous Buried Archaeological Features Using Multisensor Data from Unmanned Aerial Vehicles. Remote. Sens. 12(1), 41, 10.3390/rs12010041, BibTeX
  77. Jian Lin, Guan-hua Du, and Zhiyong Tian (2020). Interval Intuitionistic Fuzzy Clustering Algorithm Based on Symmetric Information Entropy. Symmetry 12(1), 79, 10.3390/SYM12010079, BibTeX
  78. X. Han, C. Armenakis, and M. Jadidi (2020). Dbscan Optimization For Improving Marine Trajectory Clustering And Anomaly Detection. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B4-2020, 455-461, Copernicus GmbH, 10.5194/isprs-archives-xliii-b4-2020-455-2020
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  82. Mo Tiwari, Martin Jinye Zhang, James Mayclin, Sebastian Thrun, Chris Piech, and Ilan Shomorony (2020). Bandit-PAM: Almost Linear Time k-Medoids Clustering via Multi-Armed Bandits. CoRR abs/2006.06856, BibTeX
  83. Lukas Ruff, Jacob R. Kauffmann, Robert A. Vandermeulen, Grégoire Montavon, Wojciech Samek, Marius Kloft, Thomas G. Dietterich, and Klaus-Robert Müller (2020). A Unifying Review of Deep and Shallow Anomaly Detection. CoRR abs/2009.11732, BibTeX
  84. Michael Blumenschein (2020). Pattern-Driven Design of Visualizations for High-Dimensional Data. University of Konstanz, Germany, BibTeX
  85. Сергій Францович Смерічевський, Serhii Frantsovych Smerichevskyi, Л. В. Савченко, and L.V. Savchenko (2020). Clusterization of urban territory for building an effective delivery sustem (Кластеризація міської території для побудови ефективної системи доставки). Wydawnictwo naukowe WSPIA, м. Познань, 978-83-60038-76-5
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  87. Axel Elmarsson, and Johan Grundberg (2020). A comparison of different R-tree construction techniques for range queries on neuromorphological data.
  88. Ayşegül Selvi (2020). Bilecik ilinde ilköğretimden liseye geçiş sınavlarında makine öğrenmesi yöntemleri ile öğrenci başarısının tahmini (Predicting student achievement with machine learning methods in transition from primary to high school exams in Bi̇leci̇k province). Bilecik Şeyh Edebali Üniversitesi, Fen Bilimleri Enstitüsü
  89. Chen Luo (2020). Some Rare LSH Gems for Large-scale Machine Learning. Rice University
  90. Doney Abraham (2020). Application of Machine Learning in IoT enabled Smart Grids for Attack Detection. NTNU
  91. Fatih Uzun (2020). Multidisciplinary investigation of C-Type composite sandwich radome panels within the scope of acoustic emission based damage characterization and electromagnetic transmission performance.
  92. Gabriel Matas Barceló (2020). Introducció a l’anàlisi de dades damunt una SmartPlatform. Universitat de les Illes Balears
  93. Georgios Kaiafas (2020). Ensemble Learning For Anomaly Detection With Applications For Cybersecurity And Telecommunication. University of Luxembourg, ​​Luxembourg
  94. James Luke Coyte (2020). Seated Whole Body Vibration Modelling using Inertial Motion Sensors. University of Wollongong
  95. Jennifer Carmen Frey (2020). Using data mining to repurpose German language corpora. An evaluation of data-driven analysis methods for corpus linguistics. alma
  96. Mohaddeseh Peyro (2020). The Role of FG Nucleoporins Amino Acid Sequence Composition in Nucleocytoplasmic Transport. UC Berkeley
  97. Pham Van Huong, Le Thi Hong Van, and Pham Sy Nguyen (2020). Detecting Web Attacks Based on Clustering Algorithm and Multi-branch CNN. Journal of Science and Technology on Information security 2(12), 31-37
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  100. Παναγιώτης Κεχαγιάς (2020). Σχεδιασμός και ανάπτυξη παράλληλου αλγόριθμου συσταδοποίησης στο Apache Spark (Design and development of a parallel clustering algorithm on top of Apache Spark).

2019

  1. Piotr A. Kowalski, Szymon Lukasik, Malgorzata Charytanowicz, and Piotr Kulczycki (2019). Nature Inspired Clustering - Use Cases of Krill Herd Algorithm and Flower Pollination Algorithm. Interactions Between Computational Intelligence and Mathematics (2), 83-98, Springer, 10.1007/978-3-030-01632-6_6, BibTeX
  2. Dipesh Pradhan, and Feroz Zahid (2019). Data Center Clustering for Geographically Distributed Cloud Deployments. AINA Workshops, 1030-1040, Springer, 10.1007/978-3-030-15035-8_101, BibTeX
  3. Zhong Zhang, Chongming Gao, Chongzhi Liu, Qinli Yang, and Junming Shao (2019). Towards Robust Arbitrarily Oriented Subspace Clustering. DASFAA (1), 276-291, Springer, 10.1007/978-3-030-18576-3_17, BibTeX
  4. Altamir Gomes Bispo Junior, and Robson Leonardo Ferreira Cordeiro (2019). Fast and Scalable Outlier Detection with Metric Access Methods. ICCS (2), 189-203, Springer, 10.1007/978-3-030-22741-8_14, BibTeX
  5. Daniel Popovic, Edouard Fouché, and Klemens Böhm (2019). Unsupervised Artificial Neural Networks for Outlier Detection in High-Dimensional Data. ADBIS, 3-19, Springer, 10.1007/978-3-030-28730-6_1, BibTeX
  6. Shuai Wang, Lei Hou, and Meihan Tong (2019). Unsupervised Cross-Lingual Sentence Representation Learning via Linguistic Isomorphism. KSEM (2), 215-226, Springer, 10.1007/978-3-030-29563-9_20, BibTeX
  7. Erich Schubert, and Peter J. Rousseeuw (2019). Faster k-Medoids Clustering: Improving the PAM, CLARA, and CLARANS Algorithms. SISAP, 171-187, Springer, 10.1007/978-3-030-32047-8_16, BibTeX
  8. Maximilian Archimedes Xaver Hünemörder, Daniyal Kazempour, Peer Kröger, and Thomas Seidl (2019). SIDEKICK: Linear Correlation Clustering with Supervised Background Knowledge. SISAP, 221-230, Springer, 10.1007/978-3-030-32047-8_20, BibTeX
  9. Srikanth Thudumu, Philip Branch, Jiong Jin, and Jugdutt Jack Singh (2019). Adaptive Clustering for Outlier Identification in High-Dimensional Data. ICA3PP (2), 215-228, Springer, 10.1007/978-3-030-38961-1_19, BibTeX
  10. Sudarshan S. Chawathe (2019). Clustering Blockchain Data. Unsupervised and Semi-Supervised Learning, 43-72, Springer, 10.1007/978-3-319-97864-2_3
  11. Dilip Singh Sisodia, Rahul Borkar, and Hari Shrawgi (2019). Performance Evaluation of Large Data Clustering Techniques on Web Robot Session Data. Machine Intelligence and Signal Analysis, 545-553, Springer, 10.1007/978-981-13-0923-6_47
  12. Bilkis Jamal Ferdosi, and Muhammad Masud Tarek (2019). Visual Verification and Analysis of Outliers Using Optimal Outlier Detection Result by Choosing Proper Algorithm and Parameter. Emerging Technologies in Data Mining and Information Security, 507-517, Springer, 10.1007/978-981-13-1498-8_45
  13. Liefa Liao, and Bin Luo (2019). Entropy Isolation Forest Based on Dimension Entropy for Anomaly Detection. Computational Intelligence and Intelligent Systems, 365-376, Springer, 10.1007/978-981-13-6473-0_32
  14. C.S.R. Prabhu, Aneesh Sreevallabh Chivukula, Aditya Mogadala, Rohit Ghosh, and L.M. Jenila Livingston (2019). Big Data Analytics: Systems, Algorithms, Applications. Springer, 10.1007/978-981-15-0094-7
  15. C.S.R. Prabhu, Aneesh Sreevallabh Chivukula, Aditya Mogadala, Rohit Ghosh, and L.M. Jenila Livingston (2019). Intelligent Systems. Big Data Analytics: Systems, Algorithms, Applications, 25-46, Springer, 10.1007/978-981-15-0094-7_2
  16. Laura Aquilanti, Simone Cacace, Fabio Camilli, and Raul De Maio (2019). A Mean Field Games approach to Cluster Analysis. CoRR abs/1907.02261, 10.1007/s00245-019-09646-2, BibTeX
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  18. Félix Iglesias, Tanja Zseby, Daniel C. Ferreira, and Arthur Zimek (2019). MDCGen: Multidimensional Dataset Generator for Clustering. J. Classif. 36(3), 599-618, 10.1007/S00357-019-9312-3, BibTeX
  19. Daniyal Kazempour, Markus Mauder, Peer Kröger, and Thomas Seidl (2019). Detecting global hyperparaboloid correlated clusters: a Hough-transform based multicore algorithm. Distributed Parallel Databases 37(1), 39-72, 10.1007/s10619-018-7246-0, BibTeX
  20. Ingmar Wiese, Nicole Sarna, Lena Wiese, Araek Tashkandi, and Ulrich Sax (2019). Concept acquisition and improved in-database similarity analysis for medical data. Distributed Parallel Databases 37(2), 297-321, 10.1007/s10619-018-7249-x, BibTeX
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  28. K. Dingle, A. Zimek, F. Azizieh, and A. R. Ansari (2019). Establishing a many-cytokine signature via multivariate anomaly detection. Scientific Reports 9(1), Springer Science and Business Media LLC, 10.1038/s41598-019-46097-9
  29. Apostolos A. Karanastasis, Gopal S. Kenath, Ravishankar Sundararaman, and Chaitanya K. Ullal (2019). Quantification of functional crosslinker reaction kinetics via super-resolution microscopy of swollen microgels. Soft Matter 15(45), 9336-9342, Royal Society of Chemistry (RSC), 10.1039/C9SM01618J
  30. Pedro Henrique Batista Ruas da Silveira, Alan D. Machado, Michelle C. Silva, Magali R. G. Meireles, Ana Maria Pereira Cardoso, Luis Enrique Zárate, and Cristiane Neri Nobre (2019). Identification and characterisation of Facebook user profiles considering interaction aspects. Behav. Inf. Technol. 38(8), 858-872, 10.1080/0144929X.2019.1566498, BibTeX
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  34. Maycon Leone Maciel Peixoto, Erick Roseira Pinheiro, Tácito Trindade de Araújo Tiburtino Neves, and Danilo Barbosa Coimbra (2019). Multidimensional Projections Analysis Using Performance Evaluation Planning. BRACIS, 156-161, IEEE, 10.1109/BRACIS.2019.00036, BibTeX
  35. Preeti Mishra, Vijay Varadharajan, Udaya Kiran Tupakula, and Emmanuel S. Pilli (2019). A Detailed Investigation and Analysis of Using Machine Learning Techniques for Intrusion Detection. IEEE Commun. Surv. Tutorials 21(1), 686-728, 10.1109/COMST.2018.2847722, BibTeX
  36. B.S.A.S. Rajita, and Subhrakanta Panda (2019). Community Detection Techniques for Evolving Social Networks. 2019 9th International Conference on Cloud Computing, Data Science & Engineering (Confluence), IEEE, 10.1109/CONFLUENCE.2019.8776896
  37. Arian Soltani, Behzad Akbari, and Nader Mokari (2019). User Profile-based Caching in 5G Telco-CDNs. CloudNet, 1-6, IEEE, 10.1109/CloudNet47604.2019.9064113, BibTeX
  38. Ömer Ibrahim Erduran, Mirjam Minor, Lars Hedrich, Ahmad Tarraf, Frederik Ruehl, and Hans Schroth (2019). Multi-agent Learning for Energy-Aware Placement of Autonomous Vehicles. ICMLA, 1671-1678, IEEE, 10.1109/ICMLA.2019.00273, BibTeX
  39. Abdelwahab Boualouache, Ridha Soua, and Thomas Engel (2019). VPGA: An SDN-based Location Privacy Zones Placement Scheme for Vehicular Networks. IPCCC, 1-8, IEEE, 10.1109/IPCCC47392.2019.8958746, BibTeX
  40. Attila Tiba, Zsombor Bartik, Henrietta Tomán, and András Hajdu (2019). Detecting outlier and poor quality medical images with an ensemble-based deep learning system. ISPA, 99-104, IEEE, 10.1109/ISPA.2019.8868911, BibTeX
  41. Tommaso Zoppi, Andrea Ceccarelli, and Andrea Bondavalli (2019). Evaluation of Anomaly Detection Algorithms Made Easy with RELOAD. ISSRE, 446-455, IEEE, 10.1109/ISSRE.2019.00051, BibTeX
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  44. Punit Rathore, Dheeraj Kumar, James C. Bezdek, Sutharshan Rajasegarar, and Marimuthu Palaniswami (2019). A Rapid Hybrid Clustering Algorithm for Large Volumes of High Dimensional Data. IEEE Trans. Knowl. Data Eng. 31(4), 641-654, 10.1109/TKDE.2018.2842191, BibTeX
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  93. Boleslo Edward Romero (2019). Identifying Geographical Features with Spatial Data: Multi-scale Approaches for Representing Local Extrema. UC Santa Barbara
  94. Denis A. SYROMYATNIKOV, Darya A. PYATKINA, Larisa N. KONDRATENKO, Sergey I. KRIVOLAPOV, and Diana I. STEPANOVA (2019). Big data analysis for studying water supply and sanitation coverage in cities. Revista ESPACIOS 40(27)
  95. Emeli Pettersson, and Albin Carlson (2019). Att hitta en nål i en höstack: Metoder och tekniker för att sålla och gradera stora mängder ostrukturerad textdata (Finding a Needle in a Haystack: Methods and techniques for screening and grading large amounts of unstructured textual data). Malmö universitet/Teknik och samhälle
  96. Guansong Pang (2019). Non-IID outlier detection with coupled outlier factors.
  97. Hatice AKTAŞ GÖKÇE (2019). Yapay Sinir Ağları ile Robotik Cerrahi Operasyonu Geçirmiş Prostat Kanserli Bireylerde Nüks Durumunun İncelenmesi (Investigation of the Recurrence Status in Prostate Cancer Individuals with Robotic Surgery with Artificial Neural Network). Ankara Yıldırım Beyazıt Üniversitesi Sağlık Bilimleri Enstitüsü
  98. Igor Wescley Silva de Freitas (2019). Um estudo comparativo de técnicas de detecção de outliers no contexto de classificação de dados. Universidade Federal Rural do Semi-Árido
  99. José David Jácome Escobar, and Estalin Augusto Viracocha Andrade (2019). Desarrollo de una aplicación para detección de patrones en imágenes mediante el uso de aprendizaje profundo. Quito: UCE
  100. Lars Jürgensen (2019). Clustering and Analysis of User Behaviors utilizing a Graph Edit Distance Metric. 48, Kiel University
  101. M. Mahmoudi, and نگین دانشپور (2019). A Distributed Solution for Mixed Big Data Clustering. Nashriyyah -i Muhandisi -i Barq va Muhandisi -i Kampyutar -i Iran 66(3), 169, Iranian Research Institute for Electrical Engineering
  102. Marie Ernst (2019). Contributions to spatial data analysis and Stein’s method. Université de Liège, ​Liège, ​​Belgique
  103. Marián Lamr (2019). Včasné varování před zvýšeným rizikem vzniku dopravní nehody s využitím data miningu.
  104. Matthew C. Recker (2019). Enabling Mobile Neutron Detection Systems with CLYC. Air Force Institute of Technology
  105. Morteza Mousavi Barroudi (2019). Spatio-Temporal Partitioning and Location Prediction in GPS Trajectory Data.
  106. Patrícia Freitas Pelozo Hespanhol (2019). Análise de padrões na produção de cana de açúcar utilizando aprendizado de máquina (Analysis on sugar cane production using machine learning). Universidade Estadual Paulista (UNESP)
  107. Sebastian Letschert (2019). Quantitative Analysis of Membrane Components using Super-Resolution Microscopy. Universität Würzburg, Fakultät für Biologie
  108. Xiao Yi, Mircea Scutariu, and Kenneth Smith (2019). Optimisation of offshore wind farm inter-array collection system. IET Renewable Power Generation 13(11), 1990-1999, IET Digital Library
  109. Yikai Gong (2019). A big data infrastructure for real-time traffic analytics on the cloud.
  110. Παναγιώτης Διέννης, and Αλέξανδρος Μπολοβίνος (2019). Εργαλεία ανάλυσης και οπτικοποίησης δεδομένων σε συστήματα επιχειρηματικής ευφυΐας. ΤΕΙ Δυτικής Ελλάδας
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  113. 丁志成, DING Zhicheng, 葛洪伟, GE Hongwei, 周竞, and ZHOU Jing (2019). 基于Kl散度的密度峰值聚类算法. 重庆邮电大学学报(自然科学版)
  114. 程绵绵, CHENG Mianmian, 孙群, SUN Qun, 李少梅, LI Shaomei, 徐立, and XU Li (2019). 顾及密度对比的多层次聚类点群选取方法. 武汉大学学报·信息科学版

2018

  1. Arthur Zimek, and Peter Filzmoser (2018). There and back again: Outlier detection between statistical reasoning and data mining algorithms. WIREs Data Mining Knowl. Discov. 8(6), 10.1002/widm.1280, BibTeX
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  3. Mark Wickham (2018). Machine Learning Environments. Practical Java Machine Learning, 227-295, Apress, 10.1007/978-1-4842-3951-3_5
  4. Huixiao Hong, Jieqiang Zhu, Minjun Chen, Ping Gong, Chaoyang Zhang, and Weida Tong (2018). Quantitative Structure–Activity Relationship Models for Predicting Risk of Drug-Induced Liver Injury in Humans. Drug-Induced Liver Toxicity, 77-100, Springer, 10.1007/978-1-4939-7677-5_5
  5. Adam Byron (2018). Proteomic Profiling of Integrin Adhesion Complex Assembly. Methods in Molecular Biology, 193-236, Springer, 10.1007/978-1-4939-7759-8_13
  6. Michael E. Houle, Erich Schubert, and Arthur Zimek (2018). On the Correlation Between Local Intrinsic Dimensionality and Outlierness. SISAP, 177-191, Springer, 10.1007/978-3-030-02224-2_14, BibTeX
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  8. Arno G. Stefani, Achim Sandmann, Andreas Burkovski, Johannes B. Huber, Heinrich Sticht, and Christophe Jardin (2018). Application of Methods from Information Theory in Protein-Interaction Analysis. Lecture Notes in Bioengineering, 293-313, Springer, 10.1007/978-3-319-54729-9_13
  9. Helmut Neukirchen (2018). Elephant Against Goliath: Performance of Big Data Versus High-Performance Computing DBSCAN Clustering Implementations. Simulation Science, 251-271, Springer, 10.1007/978-3-319-96271-9_16
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  11. Alberto Fernández, Salvador García, Mikel Galar, Ronaldo C. Prati, Bartosz Krawczyk, and Francisco Herrera (2018). Data Intrinsic Characteristics. Learning from Imbalanced Data Sets, 253-277, Springer, 10.1007/978-3-319-98074-4_10
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2017

  1. Abdulrahman H. Altalhi, José María Luna, M. A. Vallejo, and Sebastián Ventura (2017). Evaluation and comparison of open source software suites for data mining and knowledge discovery. WIREs Data Mining Knowl. Discov. 7(3), 10.1002/widm.1204, BibTeX
  2. Xin Jin, and Jiawei Han (2017). K-Medoids Clustering. Encyclopedia of Machine Learning and Data Mining, 697-700, Springer, 10.1007/978-1-4899-7687-1_432, BibTeX
  3. Peer Kröger, and Arthur Zimek (2017). Subspace Clustering Techniques. Encyclopedia of Database Systems, 1-4, Springer, 10.1007/978-1-4899-7993-3_607-2
  4. Adam Byron (2017). Clustering and Network Analysis of Reverse Phase Protein Array Data. Molecular Profiling, 171-191, Springer, 10.1007/978-1-4939-6990-6_12
  5. Charu C. Aggarwal (2017). Applications of Outlier Analysis. Outlier Analysis, 399-422, Springer, 10.1007/978-3-319-47578-3_13
  6. Charu C. Aggarwal, and Saket Sathe (2017). Variance Reduction in Outlier Ensembles. Outlier Ensembles, 75-161, Springer, 10.1007/978-3-319-54765-7_3
  7. Jakub Sawicki, Maciej Smolka, Marcin Los, Robert Schaefer, and Piotr Faliszewski (2017). Two-Phase Strategy Managing Insensitivity in Global Optimization. EvoApplications (1), 266-281, 10.1007/978-3-319-55849-3_18, BibTeX
  8. Christian Beilschmidt, Thomas Fober, Michael Mattig, and Bernhard Seeger (2017). Quality Measures for Visual Point Clustering in Geospatial Mapping. W2GIS, 153-168, 10.1007/978-3-319-55998-8_10, BibTeX
  9. Lediona Nishani, and Marenglen Biba (2017). Randomizing Greedy Ensemble Outlier Detection with GRASP. CISIS, 974-983, Springer, 10.1007/978-3-319-61566-0_92, BibTeX
  10. Giannis Evagorou, and Thomas Heinis (2017). STATS - A Point Access Method for Multidimensional Clusters. DEXA (1), 352-361, Springer, 10.1007/978-3-319-64468-4_27, BibTeX
  11. Jyoti Lakhani, Ajay Khuteta, Anupama Choudhary, and Dharmesh Harwani (2017). Hierarchical Clustering-Based Algorithms and In Silico Techniques for Phylogenetic Analysis of Rhizobia. Rhizobium Biology and Biotechnology, 185-214, Springer, 10.1007/978-3-319-64982-5_10
  12. Luisa Sanz-Martínez, Alejandra Martínez-Monés, Miguel L. Bote-Lorenzo, Juan Alberto Muñoz-Cristóbal, and Yannis A. Dimitriadis (2017). Automatic Group Formation in a MOOC Based on Students’ Activity Criteria. EC-TEL, 179-193, Springer, 10.1007/978-3-319-66610-5_14, BibTeX
  13. Adnan R. Manzoor, Julia S. Mollee, Aart Tijmen van Halteren, and Michel C. A. Klein (2017). Real-Life Validation of Methods for Detecting Locations, Transition Periods and Travel Modes Using Phone-Based GPS and Activity Tracker Data. ICCCI (1), 473-483, Springer, 10.1007/978-3-319-67074-4_46, BibTeX
  14. Evelyn Kirner, Erich Schubert, and Arthur Zimek (2017). Good and Bad Neighborhood Approximations for Outlier Detection Ensembles. SISAP, 173-187, Springer, 10.1007/978-3-319-68474-1_12, BibTeX
  15. Erich Schubert, and Michael Gertz (2017). Intrinsic t-Stochastic Neighbor Embedding for Visualization and Outlier Detection - A Remedy Against the Curse of Dimensionality?. SISAP, 188-203, Springer, 10.1007/978-3-319-68474-1_13, BibTeX
  16. Ankita Roy, Soumya Ray, and Radha Tamal Goswami (2017). Approaches and Challenges of Big Data Analytics—Study of a Beginner. Proceedings of the First International Conference on Intelligent Computing and Communication, 237-245, Springer, 10.1007/978-981-10-2035-3_25
  17. Brij B. Gupta, Aakanksha Tewari, Ankit Kumar Jain, and Dharma P. Agrawal (2017). Fighting against phishing attacks: state of the art and future challenges. Neural Comput. Appl. 28(12), 3629-3654, 10.1007/s00521-016-2275-y, BibTeX
  18. Hans-Peter Kriegel, Erich Schubert, and Arthur Zimek (2017). The (black) art of runtime evaluation: Are we comparing algorithms or implementations?. Knowl. Inf. Syst. 52(2), 341-378, 10.1007/s10115-016-1004-2, BibTeX
  19. Junming Shao, Xinzuo Wang, Qinli Yang, Claudia Plant, and Christian Böhm (2017). Synchronization-based scalable subspace clustering of high-dimensional data. Knowl. Inf. Syst. 52(1), 83-111, 10.1007/s10115-016-1013-1, BibTeX
  20. Johannes Schneider, and Michail Vlachos (2017). Scalable density-based clustering with quality guarantees using random projections. Data Min. Knowl. Discov. 31(4), 972-1005, 10.1007/s10618-017-0498-x, BibTeX
  21. Klaus Arthur Schmid, Andreas Züfle, Tobias Emrich, Matthias Renz, and Reynold Cheng (2017). Uncertain Voronoi cell computation based on space decomposition. GeoInformatica 21(4), 797-827, 10.1007/S10707-017-0293-2, BibTeX
  22. Mohamed Ben Khalifa, Rebeca P. Díaz Redondo, Ana Fernández Vilas, and Sandra Servia Rodríguez (2017). Identifying urban crowds using geo-located Social media data: a Twitter experiment in New York City. J. Intell. Inf. Syst. 48(2), 287-308, 10.1007/s10844-016-0411-x, BibTeX
  23. Kai Ming Ting, Takashi Washio, Jonathan R. Wells, and Sunil Aryal (2017). Defying the gravity of learning curve: a characteristic of nearest neighbour anomaly detectors. Mach. Learn. 106(1), 55-91, 10.1007/s10994-016-5586-4, BibTeX
  24. Seyed Morteza Mousavi, Aaron Harwood, Shanika Karunasekera, and Mojtaba Maghrebi (2017). Geometry of interest (GOI): spatio-temporal destination extraction and partitioning in GPS trajectory data. J. Ambient Intell. Humaniz. Comput. 8(3), 419-434, 10.1007/s12652-016-0400-5, BibTeX
  25. Michalis Korakakis, Evaggelos Spyrou, Phivos Mylonas, and Stavros J. Perantonis (2017). Exploiting social media information toward a context-aware recommendation system. Soc. Netw. Anal. Min. 7(1), 42:1-42:20, 10.1007/s13278-017-0459-9, BibTeX
  26. Susanna Spinsante, Vera Stara, Elisa Felici, Laura Montanini, Laura Raffaeli, Lorena Rossi, and Ennio Gambi (2017). The Human Factor in the Design of Successful Ambient Assisted Living Technologies. Ambient Assisted Living and Enhanced Living Environments, 61-89, Elsevier, 10.1016/B978-0-12-805195-5.00004-1
  27. Julien F. Marquant, Ralph Evins, L. Andrew Bollinger, and Jan Carmeliet (2017). A holarchic approach for multi-scale distributed energy system optimisation. Applied Energy 208, 935-953, Elsevier BV, 10.1016/j.apenergy.2017.09.057
  28. Emre Güngör, and Ahmet Özmen (2017). Distance and density based clustering algorithm using Gaussian kernel. Expert Syst. Appl. 69, 10-20, 10.1016/j.eswa.2016.10.022, BibTeX
  29. William M. Trochim (2017). Hindsight is 20/20: Reflections on the evolution of concept mapping. Evaluation and Program Planning 60, 176-185, Elsevier BV, 10.1016/j.evalprogplan.2016.08.009
  30. Elyse Allender, and Tomasz F. Stepinski (2017). Automatic, exploratory mineralogical mapping of CRISM imagery using summary product signatures. Icarus 281, 151-161, Elsevier BV, 10.1016/j.icarus.2016.08.022
  31. Sirisup Laohakiat, Suphakant Phimoltares, and Chidchanok Lursinsap (2017). A clustering algorithm for stream data with LDA-based unsupervised localized dimension reduction. Inf. Sci. 381, 104-123, 10.1016/j.ins.2016.11.018, BibTeX
  32. Francesco Gullo, Giovanni Ponti, Andrea Tagarelli, and Sergio Greco (2017). An information-theoretic approach to hierarchical clustering of uncertain data. Inf. Sci. 402, 199-215, 10.1016/j.ins.2017.03.030, BibTeX
  33. Giuseppe Rizzo, Rosa Meo, Ruggero G. Pensa, Giacomo Falcone, and Raphaël Troncy (2017). Shaping City Neighborhoods Leveraging Crowd Sensors. Inf. Syst. 64, 368-378, 10.1016/j.is.2016.06.009, BibTeX
  34. Alvin Chiang, Esther David, Yuh-Jye Lee, Guy Leshem, and Yi-Ren Yeh (2017). A study on anomaly detection ensembles. J. Appl. Log. 21, 1-13, 10.1016/j.jal.2016.12.002, BibTeX
  35. Dominik Sacha, Michael Sedlmair, Leishi Zhang, John Aldo Lee, Jaakko Peltonen, Daniel Weiskopf, Stephen C. North, and Daniel A. Keim (2017). What you see is what you can change: Human-centered machine learning by interactive visualization. Neurocomputing 268, 164-175, 10.1016/j.neucom.2017.01.105, BibTeX
  36. Linlin Zong, Xianchao Zhang, Long Zhao, Hong Yu, and Qianli Zhao (2017). Multi-view clustering via multi-manifold regularized non-negative matrix factorization. Neural Networks 88, 74-89, 10.1016/j.neunet.2017.02.003, BibTeX
  37. Marcin Los, Jakub Sawicki, Maciej Smolka, and Robert Schaefer (2017). Memetic approach for irremediable ill-conditioned parametric inverse problems. ICCS, 867-876, Elsevier, 10.1016/j.procs.2017.05.007, BibTeX
  38. Hannes Bitto, Beatrice Mörstedt, Sylvia Faschina, and Rolf-Dieter Stieglitz (2017). ADHS bei Erwachsenen. Ein dimensionales oder kategoriales Konstrukt?. Zeitschrift für Psychiatrie, Psychologie und Psychotherapie 65(2), 121-131, Hogrefe Publishing Group, 10.1024/1661-4747/a000311
  39. Wenying Ji, Simaan M. AbouRizk, Osmar R. Zaïane, and Yitong Li (2017). A Hybrid Data Mining Approach for Product Complexity Analysis. CoRR abs/1710.10555, 10.1061/(ASCE)CO.1943-7862.0001520, BibTeX
  40. Ricardo de Souza Jacomini, David Correa Martins Jr., Felipe Leno da Silva, and Anna Helena Reali Costa (2017). GeNICE: A Novel Framework for Gene Network Inference by Clustering, Exhaustive Search, and Multivariate Analysis. J. Comput. Biol. 24(8), 809-830, 10.1089/cmb.2017.0022, BibTeX
  41. Fernando Perez-Sanz, Pedro J. Navarro, and Marcos Egea-Cortines (2017). Plant phenomics: an overview of image acquisition technologies and image data analysis algorithms. GigaScience 6(11), Oxford University Press (OUP), 10.1093/gigascience/gix092
  42. Tshepiso Mokoena, Ofentswe Lebogo, Asive Dlaba, and Vukosi N. Marivate (2017). Bringing sequential feature explanations to life. AFRICON, 59-64, IEEE, 10.1109/AFRCON.2017.8095456, BibTeX
  43. Zhipeng Gao, Yang Zhao, Kun Niu, and Yidan Fan (2017). A High-Dimensional Outlier Detection Algorithm Base on Relevant Subspace. DASC/PiCom/DataCom/CyberSciTech, 1001-1008, IEEE, 10.1109/DASC-PICom-DataCom-CyberSciTec.2017.165, BibTeX
  44. Weiyu Huang, and Alejandro Ribeiro (2017). Axiomatic hierarchical clustering given intervals of metric distances. ICASSP, 4227-4231, IEEE, 10.1109/ICASSP.2017.7952953, BibTeX
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  47. Roselyn Isimeto, Chika Yinka-Banjo, Charles O. Uwadia, and Daniel C. Alienyi (2017). An enhanced clustering analysis based on glowworm swarm optimization. 2017 IEEE 4th International Conference on Soft Computing & Machine Intelligence (ISCMI) 1, 42-49, IEEE, 10.1109/ISCMI.2017.8279595
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  49. Dimitra Papadimitriou, Georgia Koutrika, Yannis Velegrakis, and John Mylopoulos (2017). Finding Related Forum Posts through Content Similarity over Intention-Based Segmentation. IEEE Trans. Knowl. Data Eng. 29(9), 1860-1873, 10.1109/TKDE.2017.2699965, BibTeX
  50. Wesin Alves, Daniel Martins, Ubiratan Bezerra, and Aldebaro Klautau (2017). A Hybrid Approach for Big Data Outlier Detection from Electric Power SCADA System. IEEE Latin America Transactions 15(1), 57-64, IEEE, 10.1109/TLA.2017.7827888
  51. David Ciechanowicz, Dominik Pelzer, Benedikt Bartenschlager, and Alois Knoll (2017). A Modular Power System Planning and Power Flow Simulation Framework for Generating and Evaluating Power Network Models. IEEE Transactions on Power Systems 32(3), 2214-2224, IEEE, 10.1109/TPWRS.2016.2602479
  52. Soongeol Kwon, Lewis Ntaimo, and Natarajan Gautam (2017). Optimal Day-Ahead Power Procurement With Renewable Energy and Demand Response. IEEE Transactions on Power Systems 32(5), 3924-3933, IEEE, 10.1109/TPWRS.2016.2643624
  53. Rocío B. Hubert, Ana Gabriela Maguitman, Carlos Iván Chesñevar, and Marcos A. Malamud (2017). CitymisVis: a Tool for the Visual Analysis and Exploration of Citizen Requests and Complaints. ICEGOV, 22-25, ACM, 10.1145/3047273.3047320, BibTeX
  54. Erich Schubert, Jörg Sander, Martin Ester, Hans-Peter Kriegel, and Xiaowei Xu (2017). DBSCAN Revisited, Revisited: Why and How You Should (Still) Use DBSCAN. ACM Trans. Database Syst. 42(3), 19:1-19:21, 10.1145/3068335, BibTeX
  55. Andrew Lensen, Bing Xue, and Mengjie Zhang (2017). GPGC: genetic programming for automatic clustering using a flexible non-hyper-spherical graph-based approach. GECCO, 449-456, ACM, 10.1145/3071178.3071222, BibTeX
  56. Daniyal Kazempour, Markus Mauder, Peer Kröger, and Thomas Seidl (2017). Detecting Global Hyperparaboloid Correlated Clusters Based on Hough Transform. SSDBM, 31:1-31:6, ACM, 10.1145/3085504.3085536, BibTeX
  57. Dominik Mautz, Wei Ye, Claudia Plant, and Christian Böhm (2017). Towards an Optimal Subspace for K-Means. KDD, 365-373, ACM, 10.1145/3097983.3097989, BibTeX
  58. Suhang Wang, Charu C. Aggarwal, and Huan Liu (2017). Randomized Feature Engineering as a Fast and Accurate Alternative to Kernel Methods. KDD, 485-494, ACM, 10.1145/3097983.3098001, BibTeX
  59. Wubai Zhou, Wei Xue, Ramesh Baral, Qing Wang, Chunqiu Zeng, Tao Li, Jian Xu, Zheng Liu, Larisa Shwartz, and Genady Ya. Grabarnik (2017). STAR: A System for Ticket Analysis and Resolution. KDD, 2181-2190, ACM, 10.1145/3097983.3098190, BibTeX
  60. Guansong Pang, Hongzuo Xu, Longbing Cao, and Wentao Zhao (2017). Selective Value Coupling Learning for Detecting Outliers in High-Dimensional Categorical Data. CIKM, 807-816, ACM, 10.1145/3132847.3132994, BibTeX
  61. Mattia Zeni, and Komminist Weldemariam (2017). Extracting information from newspaper archives in Africa. IBM J. Res. Dev. 61(6), 12:1-12:12, 10.1147/JRD.2017.2742706, BibTeX
  62. Zhihua Li, Ziyuan Li, Ning Yu, and Steven Wen (2017). Locality-Based Visual Outlier Detection Algorithm for Time Series. Secur. Commun. Networks 2017, 1869787:1-1869787:10, 10.1155/2017/1869787, BibTeX
  63. Changbo Ke, Zhiqiu Huang, Fu Xiao, and Linyuan Liu (2017). Privacy Data Decomposition and Discretization Method for SaaS Services. Mathematical Problems in Engineering 2017, 1-11, Hindawi Limited, 10.1155/2017/4785142
  64. Ricardo de Souza Jacomini (2017). Inferência de redes gênicas por agrupamento, busca exaustiva e análise de predição intrinsecamente multivariada. University of São Paulo, Brazil, 10.11606/T.3.2017.tde-05092017-111639, BibTeX
  65. Eugene Lemuel R. Garcia (2017). Bitcoin Transaction Tracing and Purchasing Behavior Characterization of Online Anonymous Marketplaces Using Side Channels. Carnegie Mellon University, 10.1184/R1/6723071.v1
  66. 迟荣华, 程媛, 朱素霞, 黄少滨, and 陈德运 (2017). 基于快速高斯变换的不确定数据聚类算法. 通信学报 38(3), 101-111, 10.11959/j.issn.1000-436x.2017061
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  68. Guillaume Casanova, Elias Englmeier, Michael E. Houle, Peer Kröger, Michael Nett, Erich Schubert, and Arthur Zimek (2017). Dimensional Testing for Reverse k-Nearest Neighbor Search. Proc. VLDB Endow. 10(7), 769-780, 10.14778/3067421.3067426, BibTeX
  69. Lu Chen, Yunjun Gao, Baihua Zheng, Christian S. Jensen, Hanyu Yang, and Keyu Yang (2017). Pivot-based Metric Indexing. Proc. VLDB Endow. 10(10), 1058-1069, 10.14778/3115404.3115411, BibTeX
  70. Burak Omer Saracoglu (2017). Location selection factors of small hydropower plant investments powered by SAW, grey WPM and fuzzy DEMATEL based on human natural language perception. International Journal of Renewable Energy Technology 8(1), 1, Inderscience Publishers, 10.1504/IJRET.2017.080867
  71. Igor A. Pestunov, Sergey A. Rylov, Yuriy N. Sinyavskiy and Vladimir B. Berikov (2017). Computationally efficient methods of clustering ensemble construction for satellite image segmentation. Collection of selected papers of the III International Conference on Information Technology and Nanotechnology, 194-200, IP Zaitsev V.D. 10.18287/1613-0073-2017-1901-194-200
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  75. Jürgen Bernard, Eduard Dobermann, Michael Sedlmair, and Dieter W. Fellner (2017). Combining Cluster and Outlier Analysis with Visual Analytics. EuroVA@EuroVis, 19-23, Eurographics Association, 10.2312/eurova.20171114, BibTeX
  76. Wubai Zhou (2017). Data Mining Techniques to Understand Textual Data. Florida International University, 10.25148/etd.FIDC003998
  77. Hinayat Sawhney and Harpreet Kaur (2017). Implementation And Applications Of Data Mining in Medical Decision Making Predictions. International Journal of Advanced Research in Computer Science 8(7), 1200-1205, IJARCS International Journal of Advanced Research in Computer Science, 10.26483/IJARCS.V8I7.4582
  78. Leonidas Tsekouras, Iraklis Varlamis, and George Giannakopoulos (2017). A Graph-based Text Similarity Measure That Employs Named Entity Information. RANLP, 765-771, INCOMA Ltd. 10.26615/978-954-452-049-6_098, BibTeX
  79. Julien F. Marquant, L. Andrew Bollinger, Ralph Evins, and Jan Carmeliet (2017). A new combined clustering method to analyse the potential of district heating networks at large-scale. 30th International Conference on Efficiency, Cost, Optimisation, Simulation and Environmental Impact of Energy Systems (ECOS 2017), ETH Zurich, 10.3929/ethz-b-000196118
  80. Yasser Abd Djawad, Andi Mu’nisa, Pangayoman Rusung, Abdi Kurniawan, Irma Suryani Idris, and Mushawwir Taiyeb (2017). Essential Feature Extraction of Photoplethysmography Signal of Men and Women in Their 20s. Engineering Journal 21(4), 259-272, Faculty of Engineering, Chulalongkorn University, 10.4186/ej.2017.21.4.259
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  83. Zachary M. Jullion (2017). A New Method for Semi-Supervised Density-Based Projected Clustering. University of Alberta, 10.7939/R3VH5CZ0S
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  99. Anthony McCaffrey, and University of Massachusetts (UMass) (2017). Feature Type Spectrum Technique.
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  110. Renzo Paranaíba Mesquita (2017). Aprimoramentos da Junção Canalizada aplicada em dados Métricos e Espaciais.
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  113. Soongeol Kwon (2017). Demand-Side Management for Energy-efficient Data Center Operations with Renewable Energy and Demand Response.
  114. Subscribers Only (2017). A Hierarchical Uncertain Clustering Method for Multi-Relational Data with Incomplete Information. Boletín Técnico, ISSN:0376-723X 55(3)
  115. Thiago Orion Simões Amorim (2017). Bioacústica de baleias cachalotes (Physeter macrocephalus Linnaeus, 1758) com ênfase no oceano Atlântico Sul ocidental. Universidade Federal de Juiz de Fora (UFJF)
  116. Vanessa Estefania Quintana Bajaña, and Sandro Anibal Yagual Tomala (2017). Propuesta de Aplicación Predictiva de Aprobación de una Asignatura con Flujo Previo a Través de Algoritmos Basados en Software WEKA Para Estudiantes del Ultimo Semestre de la Carrera de Ingeniería en Sistemas Computacionales de la Universidad de Guayaquil. Universidad de Guayaquil. Facultad de Ciencias Matematicas y Fisicas. Carrera de Ingenieria en Sistemas Computacionales
  117. Yu-Wei Liao (2017). 使用權重動態視窗之密度導向的局部離群值偵測演算法. 中興大學資訊科學與工程學系學位論文, 1-55, 中興大學
  118. Гущина Оксана Александровна (2017). Применение интеллектуальных систем при управлении рисками программных проектов. Вестник Мордовского университета 27(2), Федеральное государственное бюджетное образовательное учреждение высшего образования «Национальный исследовательский Мордовский государственный университет им. Н. П. Огарёва»
  119. Малютин Евгений Алексеевич, Бугайченко Дмитрий Юрьевич, and Мишенин Алексей Николаевич (2017). Выделение текстовых трендов в социальной сети ok. Вестник Санкт-Петербургского университета. Серия 10. Прикладная математика. Информатика. Процессы управления, Федеральное государственное бюджетное образовательное учреждение высшего образования «Санкт-Петербургский государственный университет»
  120. Попов А.Д., and Гаспарян А.Н. (2017). Проблема кластеризации данных электронной компонентной базы космического применения на Python и ее решение. Актуальные проблемы авиации и космонавтики 2(13), Федеральное государственное бюджетное образовательное учреждение высшего образования «Сибирский государственный университет науки и технологий имени академика М.Ф. Решетнева»

2016

  1. Joy Mustafi (2016). Natural Language Processing and Machine Learning for Big Data. Techniques and Environments for Big Data Analysis, 53-74, Springer, 10.1007/978-3-319-27520-8_4
  2. Johannes Blömer, and Kathrin Bujna (2016). Adaptive Seeding for Gaussian Mixture Models. PAKDD (2), 296-308, Springer, 10.1007/978-3-319-31750-2_24, BibTeX
  3. Amin Aghaee, Mehrdad Ghadiri, and Mahdieh Soleymani Baghshah (2016). Active Distance-Based Clustering Using K-Medoids. PAKDD (1), 253-264, Springer, 10.1007/978-3-319-31753-3_21, BibTeX
  4. Smita Chormunge, and Sudarson Jena (2016). Performance Efficiency and Effectiveness of Clustering Methods for Microarray Datasets. Proceedings of 3rd International Conference on Advanced Computing, Networking and Informatics, 557-567, Springer, 10.1007/978-81-322-2529-4_58
  5. Guilherme Oliveira Campos, Arthur Zimek, Jörg Sander, Ricardo J. G. B. Campello, Barbora Micenková, Erich Schubert, Ira Assent, and Michael E. Houle (2016). On the evaluation of unsupervised outlier detection: measures, datasets, and an empirical study. Data Min. Knowl. Discov. 30(4), 891-927, 10.1007/s10618-015-0444-8, BibTeX
  6. Bo Jiang, Feiyue Qiu, and Liping Wang (2016). Multi-view clustering via simultaneous weighting on views and features. Appl. Soft Comput. 47, 304-315, 10.1016/j.asoc.2016.06.010, BibTeX
  7. Manal T. Adham, and Peter J. Bentley (2016). Evaluating clustering methods within the Artificial Ecosystem Algorithm and their application to bike redistribution in London. Biosyst. 146, 43-59, 10.1016/j.biosystems.2016.04.008, BibTeX
  8. Felix Stahlberg, Tim Schlippe, Stephan Vogel, and Tanja Schultz (2016). Word segmentation and pronunciation extraction from phoneme sequences through cross-lingual word-to-phoneme alignment. Comput. Speech Lang. 35, 234-261, 10.1016/J.CSL.2014.10.001, BibTeX
  9. Bo Jiang, Feiyue Qiu, Liping Wang, and Zhenjun Zhang (2016). Bi-level weighted multi-view clustering via hybrid particle swarm optimization. Inf. Process. Manag. 52(3), 387-398, 10.1016/j.ipm.2015.11.003, BibTeX
  10. Yang Zhao, Abhishek K. Shrivastava, and Kwok Leung Tsui (2016). Imbalanced classification by learning hidden data structure. IIE Transactions 48(7), 614-628, Informa UK Limited, 10.1080/0740817X.2015.1110269
  11. Anand Mehta, and Onkar Dikshit (2016). Comparative study on projected clustering methods for hyperspectral imagery classification. Geocarto International 31(3), 296-307, Informa UK Limited, 10.1080/10106049.2015.1047416
  12. Piotr Przybyla, Matthew Shardlow, Sophie Aubin, Robert Bossy, Richard Eckart de Castilho, Stelios Piperidis, John McNaught, and Sophia Ananiadou (2016). Text mining resources for the life sciences. Database J. Biol. Databases Curation 2016, 10.1093/database/baw145, BibTeX
  13. Shane Gero, Hal Whitehead, and Luke Rendell (2016). Individual, unit and vocal clan level identity cues in sperm whale codas. Royal Society Open Science 3(1), 150372, The Royal Society, 10.1098/rsos.150372
  14. Shane Gero, Anne Bøttcher, Hal Whitehead, and Peter Teglberg Madsen (2016). Socially segregated, sympatric sperm whale clans in the Atlantic Ocean. Royal Society Open Science 3(6), 160061, The Royal Society, 10.1098/rsos.160061
  15. Bo Jiang, Feiyue Qiu, Shipin Yang, and Liping Wang (2016). Evolutionary multi-objective optimization for multi-view clustering. CEC, 3308-3315, IEEE, 10.1109/CEC.2016.7744208, BibTeX
  16. Khaled M. Fouad, and Mohamed Farouk Dawood (2016). Adaptive optimized clustering for Veterans’ Administration Lung Cancer. 2016 8th Cairo International Biomedical Engineering Conference (CIBEC), 90-93, IEEE, 10.1109/CIBEC.2016.7836127
  17. MingJie Tang, Ruby Y. Tahboub, Walid G. Aref, Mikhail J. Atallah, Qutaibah M. Malluhi, Mourad Ouzzani, and Yasin N. Silva (2016). Similarity Group-by Operators for Multi-Dimensional Relational Data. ICDE, 1448-1449, IEEE, 10.1109/ICDE.2016.7498368, BibTeX
  18. Wei Ye, Samuel Maurus, Nina C. Hubig, and Claudia Plant (2016). Generalized Independent Subspace Clustering. ICDM, 569-578, IEEE, 10.1109/ICDM.2016.0068, BibTeX
  19. Dominik Mautz, Christian Böhm, and Claudia Plant (2016). Subspace Clustering Ensembles through Tensor Decomposition. ICDM Workshops, 1225-1234, IEEE, 10.1109/ICDMW.2016.0177, BibTeX
  20. Yuan Cheng, Ronghua Chi, and Suxia Zhu (2016). An uncertain data model construction method based on nonparametric estimation. 2016 IEEE International Conference on Electronic Information and Communication Technology (ICEICT), 384-389, IEEE, 10.1109/ICEICT.2016.7879722
  21. Martin Jenckel, Syed Saqib Bukhari, and Andreas Dengel (2016). anyOCR: A sequence learning based OCR system for unlabeled historical documents. ICPR, 4035-4040, IEEE, 10.1109/ICPR.2016.7900265, BibTeX
  22. Xu Han, Chee Keong Kwoh, and Jung-Jae Kim (2016). Clustering based active learning for biomedical Named Entity Recognition. IJCNN, 1253-1260, IEEE, 10.1109/IJCNN.2016.7727341, BibTeX
  23. Vinh Truong Hoang, Alice Porebski, Nicolas Vandenbroucke, and Denis Hamad (2016). LBP parameter tuning for texture analysis of lace images. IPAS, 1-6, IEEE, 10.1109/IPAS.2016.7880063, BibTeX
  24. Josua Krause, Aritra Dasgupta, Jean-Daniel Fekete, and Enrico Bertini (2016). SeekAView: An intelligent dimensionality reduction strategy for navigating high-dimensional data spaces. LDAV, 11-19, IEEE, 10.1109/LDAV.2016.7874305, BibTeX
  25. Venkatesh Kulkarni, and Manju Nanda (2016). Data driven prognosis approach for safety critical systems. 2016 IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT), 1699-1703, IEEE, 10.1109/RTEICT.2016.7808123
  26. MingJie Tang, Ruby Y. Tahboub, Walid G. Aref, Mikhail J. Atallah, Qutaibah M. Malluhi, Mourad Ouzzani, and Yasin N. Silva (2016). Similarity Group-by Operators for Multi-Dimensional Relational Data. IEEE Trans. Knowl. Data Eng. 28(2), 510-523, 10.1109/TKDE.2015.2480400, BibTeX
  27. Lei Xu, Chunxiao Jiang, Yong Ren, and Hsiao-Hwa Chen (2016). Microblog Dimensionality Reduction - A Deep Learning Approach. IEEE Trans. Knowl. Data Eng. 28(7), 1779-1789, 10.1109/TKDE.2016.2540639, BibTeX
  28. Weiyu Huang, and Alejandro Ribeiro (2016). Hierarchical Clustering Given Confidence Intervals of Metric Distances. CoRR abs/1610.04274, 10.1109/tsp.2018.2813322, BibTeX
  29. Xiaodan Hou, and Tao Zhang (2016). Unsupervised universal steganalyzer for high-dimensional steganalytic features. J. Electronic Imaging 25(6), 63016, 10.1117/1.JEI.25.6.063016, BibTeX
  30. Fabrizio Angiulli, and Fabio Fassetti (2016). Toward Generalizing the Unification with Statistical Outliers: The Gradient Outlier Factor Measure. ACM Trans. Knowl. Discov. Data 10(3), 27:1-27:26, 10.1145/2829956, BibTeX
  31. Erich Schubert, Michael Weiler, and Hans-Peter Kriegel (2016). SPOTHOT: Scalable Detection of Geo-spatial Events in Large Textual Streams. SSDBM, 8:1-8:12, ACM, 10.1145/2949689.2949699, BibTeX
  32. Hossein Hamooni, Biplob Debnath, Jianwu Xu, Hui Zhang, Guofei Jiang, and Abdullah Mueen (2016). LogMine: Fast Pattern Recognition for Log Analytics. CIKM, 1573-1582, ACM, 10.1145/2983323.2983358, BibTeX
  33. Apurva Narechania, Richard Baker, Rob DeSalle, Barun Mathema, Sergios-Orestis Kolokotronis, Barry Kreiswirth, and Paul J. Planet (2016). Clusterflock: a flocking algorithm for isolating congruent phylogenomic datasets. GigaScience 5(1), Oxford University Press (OUP), 10.1101/045773
  34. Piotr Andrzej Kowalski, Szymon Lukasik, Malgorzata Charytanowicz, and Piotr Kulczycki (2016). Clustering based on the Krill Herd Algorithm with Selected Validity Measures. FedCSIS, 79-87, IEEE, 10.15439/2016F295, BibTeX
  35. Gang Chen, Haiying Zhang, and Caiming Xiong (2016). Maximum Margin Dirichlet Process Mixtures for Clustering. AAAI, 1491-1497, AAAI Press, 10.1609/aaai.v30i1.10197, BibTeX
  36. Guansong Pang, Kai Ming Ting, David Albrecht, and Huidong Jin (2016). ZERO++: Harnessing the Power of Zero Appearances to Detect Anomalies in Large-Scale Data Sets. Journal of Artificial Intelligence Research 57, 593-620, AI Access Foundation, 10.1613/jair.5228
  37. Rajvi Kapadia, Varun Kasbekar, and Vinaya Sawant (2016). Pattern Mining of Road Traffic in Developing Countries using Spatio-Temporal Data. IJARCCE 5(12), 237-239, Tejass Publishers, 10.17148/IJARCCE.2016.51252
  38. Amit Verma, Iqbaldeep Kaur, and Amandeep Kaur (2016). Algorithmic Approach to Data Mining and Classification Techniques. Indian Journal of Science and Technology 9(28), Indian Society for Education and Environment, 10.17485/ijst/2016/v9i28/88874
  39. Corey OMeara, Leonard Schlag, Luisa Faltenbacher, and Martin Wickler (2016). ATHMoS: Automated Telemetry Health Monitoring System at GSOC using Outlier Detection and Supervised Machine Learning. SpaceOps 2016 Conference, American Institute of Aeronautics and Astronautics, 10.2514/6.2016-2347
  40. Ivano Verzola, Alessandro Donati, Jose Martinez, Matthias Schubert, and Laszlo Somodi (2016). Project Sibyl: A Novelty Detection System for Human Spaceflight Operations. 14th International Conference on Space Operations, American Institute of Aeronautics and Astronautics (AIAA), 10.2514/6.2016-2405
  41. Qingying Yu, Yonglong Luo, Chuanming Chen, and Weixin Bian (2016). Neighborhood relevant outlier detection approach based on information entropy. Intell. Data Anal. 20(6), 1247-1265, 10.3233/IDA-150301, BibTeX
  42. Huanyang Zheng, and Jie Wu (2016). Which, When, and How: Hierarchical Clustering with Human-Machine Cooperation. Algorithms 9(4), 88, 10.3390/a9040088, BibTeX
  43. Alejandro Rituerto, Henrik Andreasson, Ana C. Murillo, Achim J. Lilienthal, and José Jesús Guerrero (2016). Building an Enhanced Vocabulary of the Robot Environment with a Ceiling Pointing Camera. Sensors 16(4), 493, 10.3390/s16040493, BibTeX
  44. Merima Kulin, Carolina Fortuna, Eli De Poorter, Dirk Deschrijver, and Ingrid Moerman (2016). Data-Driven Design of Intelligent Wireless Networks: An Overview and Tutorial. Sensors 16(6), 790, 10.3390/s16060790, BibTeX
  45. Preeti Bhargava, and Ashok K. Agrawala (2016). Modeling Users’ Behavior from Large Scale Smartphone Data Collection. EAI Endorsed Trans. Context aware Syst. Appl. 3(10), e3, 10.4108/eai.12-9-2016.151677, BibTeX
  46. V. Mahalakshmi, and M. Govindarajan (2016). Comparison of Outlier Detection Methods in Diabetes Data. International Journal of Computer Applications 155(10), 28-32, Foundation of Computer Science, 10.5120/ijca2016912451
  47. Jeffrey Hudack, and Jae C. Oh (2016). Multi-Agent Sensor Data Collection with Attrition Risk. ICAPS, 166-174, AAAI Press, BibTeX
  48. Michael J. Siers, and Md Zahidul Islam (2016). RBClust: High quality class-specific clustering using rule-based classification. ESANN, BibTeX
  49. Fatemeh Riahi, and Oliver Schulte (2016). Propositionalization for Unsupervised Outlier Detection in Multi-Relational Data. FLAIRS, 448-453, AAAI Press, BibTeX
  50. Zhiruo Zhao, Chilukuri K. Mohan, and Kishan G. Mehrotra (2016). Adaptive Sampling and Learning for Unsupervised Outlier Detection. FLAIRS, 460-466, AAAI Press, BibTeX
  51. Sebastian Bothe, and Tamás Horváth (2016). The Partial Weighted Set Cover Problem with Applications to Outlier Detection and Clustering. LWDA, 335-346, CEUR-WS.org, BibTeX
  52. Johannes Schneider, and Thomas Locher (2016). Obfuscation using Encryption. CoRR abs/1612.03345, BibTeX
  53. Klaus Arthur Schmid (2016). Searching and mining in enriched geo-spatial data. Ludwig Maximilian University of Munich, Germany, BibTeX
  54. Michael Weiler (2016). Event detection in high throughput social media. Ludwig Maximilian University of Munich, Germany, BibTeX
  55. Mingjie Tang (2016). Efficient processing of similarity queries with applications. Purdue University, USA, BibTeX
  56. Simon Maag, and Hanspeter Kriesi (2016). Politicisation, conflicts and the structuring of the EU political space. Politicising Europe, Cambridge University Press, 9781107129412
  57. Ahmed Balfagih (2016). Direct Selling Business Lead Prediction by Social Media Data Mining.
  58. Alexander Fischer-Brandies (2016). Explaining Outliers in ARTigo. Ludwig-Maximilians-Universität München
  59. B. Gajewski, and T. Martyn (2016). Spatial data clustering in independent mobile environment. Measurement Automation Monitoring Vol. 62, No. 5
  60. Bruno Miguel Nunes da Silva (2016). Exploratory Cluster Analysis from Ubiquitous Data Streams using Self-Organizing Maps.
  61. Christopher Håkansson (2016). Clustering driver’s destinations - using internal evaluation to adaptively set parameters.
  62. Francisco Daniel Porras Bernárdez (2016). Extraction of User’s Stays and Transitions from GPS Logs: A Comparison of Three Spatio-Temporal Clustering Approaches.
  63. Frederic Sautter (2016). Association Rule Generation and Evaluation of Interestingness Measures for Artwork Tags. Ludwig-Maximilians-Universität München
  64. Furkan Gözükara (2016). Product Search Engine Using Product Name Recognition and Sentiment Analysis. Cukurova University
  65. G. O. Campos, A. Zimek, J. Sander, R. J. G. B. Campello, B. Micenková, E. Schubert, I. Assent, and M. E. Houle (2016). On the Evaluation of Outlier Detection: Measures, Datasets, and an Empirical Study Continued. Proceedings of the LWDA 2016 Workshops: KDML, FGWM, FGIR, and FGDB, Potsdam, Germany
  66. Helmut Neukirchen (2016). Survey and Performance Evaluation of DBSCAN Spatial Clustering Implementations for Big Data and High-Performance Computing Paradigms. Technical report VHI-01-2016, Engineering Research Institute, University of Iceland
  67. Hemlata Chahal, and Preeti Gulia (2016). Comprehensive Study of Open-Source Big Data Mining Tools. International Journal of Artificial Intelligence and Knowledge Discovery 6(1).
  68. Hrvoje Brlečić Layer (2016). Klasifikacija energetskih subjekata u Republici Hrvatskoj korištenjem otkrivanja znanja iz baza podataka. University of Zagreb. Faculty of Economics and Business.
  69. Huang Dan (2016). Design and implementation of semantic annotation system based on fragmentation knowledge. E.T.S. de Ingenieros Informáticos (UPM)
  70. Jakub Velkoborský (2016). Hierarchical visualization of the chemical space.
  71. Jeffrey Hudack (2016). Risk-Aware Planning for Sensor Data Collection. Syracuse University
  72. Joonas Puura (2016). Tarkvara loomine erinevate k-keskmiste algoritmide rakendamiseks (Software for Clustering Using k-means Algorithms).
  73. Justin Sam Chew, and Maurice HT Ling (2016). TAPPS Release 1: Plugin-Extensible Platform for Technical Analysis and Applied Statistics. Advances in Computer Science: an International Journal 5(1), 132-141
  74. Laleh Jalali (2016). Interactive Event-driven Knowledge Discovery from Data Streams. UC Irvine
  75. Luca Putelli (2016). Estrazione di regole di associazione da dati RDF. Italy
  76. Martin Jenckel, Syed Saqib Bukhari, and Andreas Dengel (2016). Clustering Benchmark for Characters in Historical Documents. DAS 2016 Short Paper Booklet, 33-34
  77. Miguel José Cavadas Santos (2016). Automated Scalable Platform for Packet Traffic Analysis.
  78. Mustafa Takaoğlu (2016). Birkaç Veri Kümesi ile WEKA ve MATLAB Üzerinde Kümeleme Algoritmalarının Karşılaştırılarak İncelenmesi. İstanbul Aydin Üni̇versi̇tesi̇ Fen Bi̇li̇mleri̇ Ensti̇tüsü
  79. N. Srujana, G. Srinivasa Rao, and M. V. Sivaprasad (2016). Unsupervised Distance-Based Outlier Detection In High Dimensional Data. IJITR 4(5), 3905–3907
  80. P.A.R. Kostjens (2016). Anomaly Detection in Application Log Data.
  81. Parvej Aalam, and Tamanna Siddiqui (2016). Comparative study of data mining tools used for clustering. 2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom), 3971-3975, IEEE
  82. Pawel Lee (2016). Structure in Star Forming Regions. University of Sheffield
  83. Ravi Chinapaga, D. Sravya, M Bal Raju, and N Subhash Chandra (2016). Detecting Outliers Using Euclidean Distance In Unsupervised Method. IJITR 4(5), 3855–3857
  84. Sebastian Rühl (2016). Event Detection in ARTigo Data. Ludwig-Maximilians-Universität München
  85. Sirisup Laohakiat (2016). Development Of Density Based Clustering Algorithms For Streaming Data (การพัฒนาขั้นตอนวิธีจัดกลุ่มบนพื้นฐานความหนาแน่นสำหรับข้อมูลที่มีการไหลเข้าอย่างต่อเนื่อง). Chulalongkorn University
  86. Stephen K Karanja (2016). Density-based Cluster Analysis Of Fire Hot Spots In Kenya’s Wildlife Protected Areas. University of Nairobi
  87. Talita de Souza Rampão (2016). Mineração de dados em bases jurídicas: um estudo de caso.
  88. Thomas Rusch, Kurt Hornik, and Patrick Mair (2016). Assessing and quantifying clusteredness: The OPTICS Cordillera. WU Vienna University of Economics and Business
  89. Tilmann Zäschke (2016). The PH-Tree Revisited r1.2.
  90. Trusina Jan (2016). Implementace evolučního shlukování. České vysoké učení technické v Praze. Vypočetní a informační centrum.
  91. Xt Nguyen (2016). Anomaly Detection in Distributed Dataflow Systems. Technische Universität Berlin
  92. 沈琰辉, 刘华文, 徐晓丹, 赵建民, and 陈中育 (2016). 基于邻域离散度的异常点检测算法. 计算机科学与探索 10(12), 1763-1772

2015

  1. Greg Hamerly, and Jonathan Drake (2015). Accelerating Lloyd’s Algorithm for k-Means Clustering. Partitional Clustering Algorithms, 41-78, Springer, 10.1007/978-3-319-09259-1_2
  2. Monika Kofler, Andreas Beham, Stefan Wagner, and Michael Affenzeller (2015). Robust Storage Assignment in Warehouses with Correlated Demand. Computational Intelligence and Efficiency in Engineering Systems, 415-428, Springer, 10.1007/978-3-319-15720-7_29, BibTeX
  3. Erich Schubert, Arthur Zimek, and Hans-Peter Kriegel (2015). Fast and Scalable Outlier Detection with Approximate Nearest Neighbor Ensembles. DASFAA (2), 19-36, Springer, 10.1007/978-3-319-18123-3_2, BibTeX
  4. Taylor Arnold, and Lauren Tilton (2015). Image Data. Humanities Data in R, 113-129, Springer, 10.1007/978-3-319-20702-5_8
  5. Markus Mauder, Markus Reisinger, Tobias Emrich, Andreas Züfle, Matthias Renz, Goce Trajcevski, and Roberto Tamassia (2015). Minimal Spatio-Temporal Database Repairs. SSTD, 255-273, Springer, 10.1007/978-3-319-22363-6_14, BibTeX
  6. Lasanthi Heendaliya, Michael Wisely, Dan Lin, Sahra Sedigh Sarvestani, and Ali R. Hurson (2015). Influence-Aware Predictive Density Queries Under Road-Network Constraints. SSTD, 80-97, Springer, 10.1007/978-3-319-22363-6_5, BibTeX
  7. Tobias Emrich, Klaus Arthur Schmid, Andreas Züfle, Matthias Renz, and Reynold Cheng (2015). Uncertain Voronoi Cell Computation Based on Space Decomposition. SSTD, 98-116, Springer, 10.1007/978-3-319-22363-6_6, BibTeX
  8. Bo Zhu, Alexandru Mara, and Alberto Mozo (2015). CLUS: Parallel Subspace Clustering Algorithm on Spark. ADBIS (Short Papers and Workshops), 175-185, Springer, 10.1007/978-3-319-23201-0_20, BibTeX
  9. Pengjie Ren, Peng Liu, Zhumin Chen, Jun Ma, and Xiaomeng Song (2015). Learning Similarity Functions for Urban Events Detection by Mining Hotline Phone Records. APWeb, 411-423, Springer, 10.1007/978-3-319-25255-1_34, BibTeX
  10. Nadezhda Fedorova, Josep Blat, and David F. Nettleton (2015). Can Embedding Solve Scalability Issues for Mixed-Data Graph Clustering?. Euro-Par Workshops, 481-492, Springer, 10.1007/978-3-319-27308-2_39, BibTeX
  11. Tobias Emrich, Hans-Peter Kriegel, Peer Kröger, Johannes Niedermayer, Matthias Renz, and Andreas Züfle (2015). On reverse-k-nearest-neighbor joins. GeoInformatica 19(2), 299-330, 10.1007/s10707-014-0215-5, BibTeX
  12. Arthur Zimek, and Jilles Vreeken (2015). The blind men and the elephant: on meeting the problem of multiple truths in data from clustering and pattern mining perspectives. Mach. Learn. 98(1-2), 121-155, 10.1007/s10994-013-5334-y, BibTeX
  13. Heiko Paulheim, and Robert Meusel (2015). A decomposition of the outlier detection problem into a set of supervised learning problems. Mach. Learn. 100(2-3), 509-531, 10.1007/s10994-015-5507-y, BibTeX
  14. Daniel Avila, and Iren Valova (2015). RADDACL2: a recursive approach to discovering density clusters. Prog. Artif. Intell. 4(1-2), 21-36, 10.1007/s13748-015-0066-9, BibTeX
  15. Tamer F. Ghanem, Wail S. El-Kilani, Hatem M. Abdelkader, and Mohiy M. Hadhoud (2015). Fast Dimension-based Partitioning and Merging clustering algorithm. Appl. Soft Comput. 36, 143-151, 10.1016/j.asoc.2015.05.049, BibTeX
  16. Antonio Lavecchia (2015). Machine-learning approaches in drug discovery: methods and applications. Drug Discovery Today 20(3), 318-331, Elsevier BV, 10.1016/j.drudis.2014.10.012
  17. Francisco Maciá Pérez, José Vicente Berná-Martínez, Alberto Fernández Oliva, and Miguel Alfonso Abreu Ortega (2015). Algorithm for the detection of outliers based on the theory of rough sets. Decis. Support Syst. 75, 63-75, 10.1016/j.dss.2015.05.002, BibTeX
  18. Mohamed Bouguessa (2015). A practical outlier detection approach for mixed-attribute data. Expert Syst. Appl. 42(22), 8637-8649, 10.1016/j.eswa.2015.07.018, BibTeX
  19. Wen-qian Liu, Jun Liu, Meng Wang, Qinghua Zheng, Wei Zhang, Lingyun Song, and Siyu Yao (2015). Faceted fusion of RDF data. Inf. Fusion 23, 16-24, 10.1016/j.inffus.2014.06.005, BibTeX
  20. Seok-Ho Yoon, Ki-Nam Kim, Jiwon Hong, Sang-Wook Kim, and Sunju Park (2015). A community-based sampling method using DPL for online social networks. Inf. Sci. 306, 53-69, 10.1016/j.ins.2015.02.014, BibTeX
  21. Bifan Wei, Jun Liu, Qinghua Zheng, Wei Zhang, Chenchen Wang, and Bei Wu (2015). DF-Miner: Domain-specific facet mining by leveraging the hyperlink structure of Wikipedia. Knowl. Based Syst. 77, 80-91, 10.1016/j.knosys.2015.01.001, BibTeX
  22. M. Peyro, M. Soheilypour, B.L. Lee, and M.R.K. Mofrad (2015). Evolutionarily Conserved Sequence Features Regulate the Formation of the FG Network at the Center of the Nuclear Pore Complex. Scientific Reports 5(1), Springer, 10.1038/srep15795
  23. Allison Reilly, and Seth Guikema (2015). Bayesian Multiscale Modeling of Spatial Infrastructure Performance Predictions with an Application to Electric Power Outage Forecasting. Journal of Infrastructure Systems 21(2), American Society of Civil Engineers (ASCE), 10.1061/%28ASCE%29IS.1943-555X.0000222
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  71. Bryan Omar Collazo Santiago (2015). Machine learning blocks. Massachusetts Institute of Technology
  72. Carl Levin, and Christopher Håkansson (2015). Clustering driver’s destinations - using internal evaluation to adaptively set parameters.
  73. Gilad Armon, Adiel Loinger, Uri Blatt, and Shahar Siegman (2015). Benchmarking In Online Advertising.
  74. Gordon O Ondego (2015). A comparative study of decision Tree and Naïve Bayesian Classifiers on Verbal Autopsy Datasets. University of Nairobi
  75. I Gusti Bagus Ady Sutrisna, Kemas Rahmat Saleh Wiharja, and Alfian Akbar Gozali (2015). Penerapan Algoritma GRAC (Graph Algorithm Clustering) untuk Graph Database Compression). eProceedings of Engineering 2(1)
  76. Irene Fernández Sánchez (2015). Diseño de una metodología de evaluación de servicios públicos basada en modelos analíticos sobre datos abiertos y de redes sociales. Telecomunicacion
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  78. Judit Kockat, and Clemens Rohde (2015). Conditions for local adaption of building policies in German cities according to their building structure and demography. ECEEE
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  82. Lasanthi Nilmini Heendaliya (2015). Enabling near-term prediction of status for intelligent transportation systems: Management techniques for data on mobile objects. Missouri University of Science and Technology
  83. Lev Aleksandrovich Kazakovtsev, Aljona Aleksandrovna Stupina, Victor Ivanovich Orlov, Margarita Vladimirovna Karaseva, and Igor Sergeevich Masich (2015). Clustering Methods For Classification Of Electronic Devices By Production Batches And Quality Classes. Facta Universitatis, Series: Mathematics and Informatics 30(5), 567-581
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2014

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  8. Kirill Smirnov, George A. Chernishev, Pavel Fedotovsky, George Erokhin, and Kirill Cherednik (2014). The Study of Multidimensional R-Tree-Based Index Scalability in Multicore Environment. Ershov Memorial Conference, 266-272, Springer, 10.1007/978-3-662-46823-4_22, BibTeX
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  47. Björn Löfroth (2014). Mobile traffic dataset comparisons throughcluster analysis of radio network event sequences.
  48. Borut Sluban (2014). Ensemble-Based Noise And Outlier Detection. Jožef Stefan International Postgraduate School
  49. Davi Felipe Russi (2014). Uso de dados de redes sociais para detecção de problemas de mobilidade urbana. Universidade Federal de Santa Maria
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  51. Florian Hoidn (2014). The Analytics Center: Devising a Citizen Science Data Mining Tool for the ARTigo Image Tagging Project. Ludwig-Maximilians-Universität München
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  53. Henrik Larsson, and Erik Lindqvist (2014). Unsupervised Outlier Detection in Software Engineering. Institutionen för data- och informationsteknik (Chalmers), Chalmers tekniska högskola
  54. Jichao Sun (2014). Local selection of features and its applications to image search and annotation. New Jersey Institute of Technology
  55. João Luiz Grave Gross (2014). URSA: um framework para agrupamento de dados e validação de resultados (URSA: a framework for data clustering and data analysis).
  56. Kaisa Vent (2014). Inimese tegevuskohtade leidmine nutitelefonipõhiste käitumisandmestike alusel. Tartu Ülikool
  57. Milan. Vukićević (2014). Razvoj i projektovanje algoritama za klasterovanje ekspresija gena (Development and design of algorithms for clustering gene expression data: doctoral dissertation). Univerzitet u Beogradu, Fakultet organizacionih nauka
  58. Monika Kofler (2014). Optimising the storage location assignment problem under dynamic conditions.
  59. Muhammad Sohail (2014). Calculation of Energy Footprint of Manufacturing Assets.
  60. Nicola Padovano, and Elia Filiberto Polo (2014). Progetto e realizzazione di un framework per Neosperience sul clustering di reti sociali. Italy
  61. Pratik Kumar Mishra, Dinesh Pothineni, Aadil Rasheed, Deepak Sundararajan, Ashok Krish, Hasit Kaji, and Tata Consultancy Services Limited (2014). System and Method for Determining an Expert of a Subject on a Web-based Platform.
  62. R.J. Ma, and N.Y. Yu (2014). A new route for energy efficiency diagnosis and potential analysis of energy consumption from air-conditioning system. Energy Systems Laboratory (http://esl.tamu.edu)
  63. Reka Katalin Kelemen (2014). Mathematical modeling of T cell clustering following malaria infection in mice. University of Tennessee, Knoxville
  64. Ritesh Shukla (2014). Machine learning ecosystem: implications for business strategy centered on machine learning. Massachusetts Institute of Technology
  65. Sheila Mollá Santiago (2014). Generalització de mètodes de density-based clustering a dades mixtes. Universitat Politècnica de Catalunya
  66. Tânia Margarida dos Santos Gomes (2014). Ferramentas open source de Data Mining.
  67. V. Ilango (2014). Forecasting Methods Based on Outlier Detection And Influential Point Observation on Clustering Techniques Using Financial Time Series Data. Virudhunagar
  68. Y.P.J.M. van Oirschot (2014). Using Trace Clustering for Configurable Process Discovery Explained by Event Log Data.
  69. И.А. Пестунов, and С.А. Рылов (2014). Метод построения ансамбля сеточных иерархических алгоритмов кластеризации для сегментации спутниковых изображений. Региональные проблемы дистанционного зондирования Земли, 215-223
  70. Казаковцев Лев Александрович, Орлов Виктор Иванович, Ступина Алена Александровна, and Масич Игорь Сергеевич (2014). Задача классификации электронной компонентной базы. Вестник Сибирского государственного университета науки и технологий имени академика М. Ф. Решетнева, Федеральное государственное бюджетное образовательное учреждение высшего образования «Сибирский государственный университет науки и технологий имени академика М.Ф. Решетнева»

2013

  1. Zeyar Aung (2013). Database Systems for the Smart Grid. Smart Grids, 151-168, Springer, 10.1007/978-1-4471-5210-1_7
  2. Charu C. Aggarwal (2013). Outlier Analysis. Springer, 10.1007/978-1-4614-6396-2, BibTeX
  3. Charu C. Aggarwal (2013). Applications of Outlier Analysis. Outlier Analysis, 373-400, Springer, 10.1007/978-1-4614-6396-2_12
  4. Charu C. Aggarwal (2013). High-Dimensional Outlier Detection: The Subspace Method. Outlier Analysis, 135-167, Springer, 10.1007/978-1-4614-6396-2_5
  5. Jordi Nin, David Carrera, and Daniel Villatoro (2013). On the Use of Social Trajectory-Based Clustering Methods for Public Transport Optimization. CitiSens, 59-70, Springer, 10.1007/978-3-319-04178-0_6, BibTeX
  6. Mark J. Embrechts, Christopher J. Gatti, Jonathan Linton, and Badrinath Roysam (2013). Hierarchical Clustering for Large Data Sets. Advances in Intelligent Signal Processing and Data Mining, 197-233, Springer, 10.1007/978-3-642-28696-4_8
  7. Mariusz Oszust, and Marian Wysocki (2013). Clustering and Classification of Time Series Representing Sign Language Words. ICAISC (2), 218-229, Springer, 10.1007/978-3-642-38610-7_21, BibTeX
  8. Rana Momtaz, Nesma Mohssen, and Mohammad A. Gowayyed (2013). DWOF: A Robust Density-Based Outlier Detection Approach. IbPRIA, 517-525, Springer, 10.1007/978-3-642-38628-2_61, BibTeX
  9. Felix Stahlberg, Tim Schlippe, Stephan Vogel, and Tanja Schultz (2013). Pronunciation Extraction from Phoneme Sequences through Cross-Lingual Word-to-Phoneme Alignment. SLSP, 260-272, Springer, 10.1007/978-3-642-39593-2_23, BibTeX
  10. Tobias Emrich, Hans-Peter Kriegel, Peer Kröger, Johannes Niedermayer, Matthias Renz, and Andreas Züfle (2013). Reverse-k-Nearest-Neighbor Join Processing. SSTD, 277-294, Springer, 10.1007/978-3-642-40235-7_16, BibTeX
  11. Erich Schubert, Arthur Zimek, and Hans-Peter Kriegel (2013). Geodetic Distance Queries on R-Trees for Indexing Geographic Data. SSTD, 146-164, Springer, 10.1007/978-3-642-40235-7_9, BibTeX
  12. Jeremy Steinhauer, Lois M. L. Delcambre, Marianne Lykke, and Marit Kristine Ådland (2013). Do User (Browse and Click) Sessions Relate to Their Questions in a Domain-Specific Collection?. TPDL, 96-107, Springer, 10.1007/978-3-642-40501-3_10, BibTeX
  13. Enikö Székely, Pascal Poncelet, Florent Masseglia, Maguelonne Teisseire, and Renaud Cezar (2013). A Density-Based Backward Approach to Isolate Rare Events in Large-Scale Applications. Discovery Science, 249-264, Springer, 10.1007/978-3-642-40897-7_17, BibTeX
  14. Xuan-Hong Dang, Barbora Micenková, Ira Assent, and Raymond T. Ng (2013). Local Outlier Detection with Interpretation. ECML/PKDD (3), 304-320, Springer, 10.1007/978-3-642-40994-3_20, BibTeX
  15. Part Pramokchon, and Punpiti Piamsa-nga (2013). An Unsupervised, Fast Correlation-Based Filter for Feature Selection for Data Clustering. DaEng, 87-94, Springer, 10.1007/978-981-4585-18-7_10, BibTeX
  16. Christophe Jardin, Arno G. Stefani, Martin Eberhardt, Johannes B. Huber, and Heinrich Sticht (2013). An information-theoretic classification of amino acids for the assessment of interfaces in protein–protein docking. Journal of Molecular Modeling 19(9), 3901-3910, Springer, 10.1007/s00894-013-1916-7
  17. Kai Ming Ting, Takashi Washio, Jonathan R. Wells, Fei Tony Liu, and Sunil Aryal (2013). DEMass: a new density estimator for big data. Knowl. Inf. Syst. 35(3), 493-524, 10.1007/s10115-013-0612-3, BibTeX
  18. Kai Ming Ting, Guang-Tong Zhou, Fei Tony Liu, and Swee Chuan Tan (2013). Mass estimation. Mach. Learn. 90(1), 127-160, 10.1007/s10994-012-5303-x, BibTeX
  19. Ibrahim Aljarah, and Simone A. Ludwig (2013). A new clustering approach based on Glowworm Swarm Optimization. IEEE Congress on Evolutionary Computation, 2642-2649, IEEE, 10.1109/CEC.2013.6557888, BibTeX
  20. Yang Zhao, and Abhishek K. Shrivastava (2013). Combating Sub-Clusters Effect in Imbalanced Classification. ICDM, 1295-1300, IEEE, 10.1109/ICDM.2013.105, BibTeX
  21. Barbora Micenková, Raymond T. Ng, Xuan-Hong Dang, and Ira Assent (2013). Explaining Outliers by Subspace Separability. ICDM, 518-527, IEEE, 10.1109/ICDM.2013.132, BibTeX
  22. Arian Bär, Antonio Paciello, and Peter Romirer-Maierhofer (2013). Trapping botnets by DNS failure graphs: Validation, extension and application to a 3G network. INFOCOM, 3159-3164, IEEE, 10.1109/INFCOM.2013.6567131, BibTeX
  23. Arian Bär, Antonio Paciello, and Peter Romirer-Maierhofer (2013). Trapping botnets by DNS failure graphs: Validation, extension and application to a 3G network. INFOCOM Workshops, 393-398, IEEE, 10.1109/INFCOMW.2013.6562863, BibTeX
  24. Amine Chaibi, Mustapha Lebbah, and Hanane Azzag (2013). A New Visualization of Group-Outliers in Unsupervised Learning. IV, 162-167, IEEE, 10.1109/IV.2013.20, BibTeX
  25. Elke Achtert, Hans-Peter Kriegel, Erich Schubert, and Arthur Zimek (2013). Interactive data mining with 3D-parallel-coordinate-trees. SIGMOD Conference, 1009-1012, ACM, 10.1145/2463676.2463696, BibTeX
  26. Arthur Zimek, Matthew Gaudet, Ricardo J. G. B. Campello, and Jörg Sander (2013). Subsampling for efficient and effective unsupervised outlier detection ensembles. KDD, 428-436, ACM, 10.1145/2487575.2487676, BibTeX
  27. Benjamin Welton, Evan Samanas, and Barton P. Miller (2013). Mr. Scan: extreme scale density-based clustering using a tree-based network of GPGPU nodes. SC, 84:1-84:11, ACM, 10.1145/2503210.2503262, BibTeX
  28. Johannes Schneider, and Michail Vlachos (2013). Fast parameterless density-based clustering via random projections. CIKM, 861-866, ACM, 10.1145/2505515.2505590, BibTeX
  29. Toon De Pessemier, Simon Dooms, and Luc Martens (2013). A food recommender for patients in a care facility. RecSys, 209-212, ACM, 10.1145/2507157.2507198, BibTeX
  30. Solen Quiniou, Peggy Cellier, Thierry Charnois, and Dominique Legallois (2013). Graph Mining under Linguistic Constraints for Exploring Large Texts. Computación y Sistemas 17(2), 239-250, 10.13053/cys-17-2-1529
  31. Charu C. Aggarwal, and Chandan K. Reddy (2013). Educational and Software Resources for Data Clustering. Data Clustering: Algorithms and Applications, 607-616, CRC Press, 10.1201/9781315373515-24, BibTeX
  32. David Ando, Michael Colvin, Michael Rexach, and Ajay Gopinathan (2013). Physical Motif Clustering within Intrinsically Disordered Nucleoporin Sequences Reveals Universal Functional Features. PLoS ONE 8(9), e73831, Public Library of Science (PLoS), 10.1371/journal.pone.0073831
  33. Martin Schäler, Alexander Grebhahn, Reimar Schröter, Sandro Schulze, Veit Köppen, and Gunter Saake (2013). QuEval: Beyond high-dimensional indexing a la carte. Proc. VLDB Endow. 6(14), 1654-1665, 10.14778/2556549.2556551, BibTeX
  34. Kai M. Ting (2013). Second Generation of Mass Estimation. Defense Technical Information Center, 10.21236/ada590623
  35. Martin Behnisch, Gotthard Meinel, Sebastian Tramsen, and Markus Diesselmann (2013). Using quadtree representations in building stock visualization and analysis. Erdkunde 67(2), 151-166, Erdkunde, 10.3112/erdkunde.2013.02.04
  36. Jai PrakashVerma, Bankim Patel, and Atul Patel (2013). Web Mining: Opinion and Feedback Analysis for Educational Institutions. International Journal of Computer Applications 84(6), 17-22, Foundation of Computer Science, 10.5120/14579-2800
  37. Arthur Zimek (2013). Clustering High-Dimensional Data. Data Clustering: Algorithms and Applications, 201-230, BibTeX
  38. Tobias Emrich, Peer Kröger, Johannes Niedermayer, Matthias Renz, and Andreas Züfle (2013). A Mutual Pruning Approach for RkNN Join Processing. BTW, 21-35, GI, BibTeX
  39. Sylvain Dormieu, and Nicolas Labroche (2013). SNOW, un algorithme exploratoire pour le subspace clustering. EGC, 79-84, Hermann-Éditions, BibTeX
  40. Jens Ehlers (2013). Self-Adaptive Performance Monitoring for Component-Based Software Systems. Softwaretechnik-Trends 33(2), BibTeX
  41. Tobias Emrich (2013). Coping with distance and location dependencies in spatial, temporal and uncertain data. Ludwig Maximilians University Munich, BibTeX
  42. Hardy Kremer (2013). Mining and similarity search in temporal databases. RWTH Aachen University, BibTeX
  43. Daniel Kuntze (2013). Practical algorithms for clustering and modeling large data sets: analysis and improvements. 1-130, University of Paderborn, BibTeX
  44. Erich Schubert (2013). Generalized and efficient outlier detection for spatial, temporal, and high-dimensional data mining. 1-262, Ludwig Maximilians University Munich, BibTeX
  45. Andreas Züfle (2013). Similarity search and mining in uncertain spatial and spatio-temporal databases. 1-397, Ludwig Maximilians University Munich, BibTeX
  46. Matthew Orlinski (2013). Neighbour discovery and distributed spatio-temporal cluster detection in pocket switched networks. University of Manchester, UK, BibTeX
  47. Claire Elizabeth Q (2013). Machine learning analysis of the cultural and cross-cultural aspects of beauty in music. Aberystwyth University, UK, BibTeX
  48. Thomas H. Davenport, and Jinho Kim (2013). Keeping Up with the Quants. Your Guide to Understanding and Using Analytics. Harvard Business Press, 9781422187265
  49. Ivanka Menken (2013). Data Mining Guidance - Real World Application, Templates, Documents, and Examples of the use of Data Mining in the Public Domain. Emereo Publishing, 9781486460458
  50. Albrecht Zimmermann (2013). Feature construction based on class outliers. CW Reports
  51. Bruno Daigle (2013). Méthodes bioinformatiques pour l’évaluation de la classification du virus du papillome humain. Université du Québec à Montréal
  52. Curdin Barandun, Stefan Derungs, and Gino Paulaitis (2013). Mixtape: Analyse und Erstellung Ähnlichkeitsanalyse von Musik anhand einer praktischen Implementation. HSR Hochschule für Technik Rapperswil
  53. Jan Vykopal (2013). Flow-based Brute-force Attack Detection in Large and High-speed Networks. Masarykova univerzita, Fakulta informatiky
  54. Jan Vykopal (2013). SimFlow - a similarity-based detection of brute-force attacks.
  55. Luiz O. Carvalho, Thatyana F. P. Seraphim, Caetano Traina Júnior, and Enzo Seraphim (2013). ObInject: a NoODMG Persistence and Indexing Framework for Object Injection. Journal of Information and Data Management 4(3), 220
  56. Manish Gupta (2013). Outlier detection for information networks. University of Illinois at Urbana-Champaign
  57. Maria José Gomes Pedroto (2013). Estimação de Massa em Energia Eólica.
  58. N Ronald (2013). Workers, adventurers, explorers: uncovering activity patterns in Melbourne. Australasian Transport Research Forum (ATRF), 36th, 2013, Brisbane, Queensland, Australia
  59. Solen Quiniou, Peggy Cellier, Thierry Charnois, and Dominique Legallois (2013). Graph Mining under Linguistic Constraints to Explore Large Texts. International Conference on Intelligent Text Processing and Computational Linguistics (CICLing’13)
  60. Stefan Eduard Raposo Alves (2013). Towards improving WEBSOM with multi-word expressions. Faculdade de Ciências e Tecnologia
  61. Vladimír Matejovský (2013). Podpora shlukování webových stránek pomocí link mining. Masarykova univerzita, Fakulta informatiky

2012

  1. Arthur Zimek, Erich Schubert, and Hans-Peter Kriegel (2012). A survey on unsupervised outlier detection in high-dimensional numerical data. Stat. Anal. Data Min. 5(5), 363-387, 10.1002/sam.11161, BibTeX
  2. Hans-Peter Kriegel, Peer Kröger, and Arthur Zimek (2012). Subspace clustering. WIREs Data Mining Knowl. Discov. 2(4), 351-364, 10.1002/widm.1057, BibTeX
  3. Charu C. Aggarwal (2012). An Introduction to Outlier Analysis. Outlier Analysis, 1-40, Springer, 10.1007/978-1-4614-6396-2_1
  4. Dawn E. Holmes, Jeffrey Tweedale, and Lakhmi C. Jain (2012). Data Mining Techniques in Clustering, Association and Classification. Data Mining: Foundations and Intelligent Paradigms, 1-6, Springer, 10.1007/978-3-642-23166-7_1
  5. Philipp Kranen, Hardy Kremer, Timm Jansen, Thomas Seidl, Albert Bifet, Geoff Holmes, Bernhard Pfahringer, and Jesse Read (2012). Stream Data Mining Using the MOA Framework. DASFAA (2), 309-313, Springer, 10.1007/978-3-642-29035-0_27, BibTeX
  6. Ira Assent, Philipp Kranen, Corinna Baldauf, and Thomas Seidl (2012). AnyOut: Anytime Outlier Detection on Streaming Data. DASFAA (1), 228-242, Springer, 10.1007/978-3-642-29038-1_18, BibTeX
  7. Eva Kühn, Alexander Marek, Thomas Scheller, Vesna Sesum-Cavic, Michael Vögler, and Stefan Craß (2012). A Space-Based Generic Pattern for Self-Initiative Load Clustering Agents. COORDINATION, 230-244, Springer, 10.1007/978-3-642-30829-1_16, BibTeX
  8. Emmanuel Müller, Fabian Keller, Sebastian Blanc, and Klemens Böhm (2012). OutRules: A Framework for Outlier Descriptions in Multiple Context Spaces. ECML/PKDD (2), 828-832, Springer, 10.1007/978-3-642-33486-3_57, BibTeX
  9. Mohamed Bouguessa (2012). Modeling Outlier Score Distributions. ADMA, 713-725, Springer, 10.1007/978-3-642-35527-1_59, BibTeX
  10. Michael Davis, Weiru Liu, and Paul C. Miller (2012). Finding the Most Descriptive Substructures in Graphs with Discrete and Numeric Labels. NFMCP, 138-154, Springer, 10.1007/978-3-642-37382-4_10, BibTeX
  11. Boris Delibasic, Milan Vukicevic, Milos Jovanovic, Kathrin Kirchner, Johannes Ruhland, and Milija Suknovic (2012). An architecture for component-based design of representative-based clustering algorithms. Data Knowl. Eng. 75, 78-98, 10.1016/j.datak.2012.03.005, BibTeX
  12. Elke Achtert, Sascha Goldhofer, Hans-Peter Kriegel, Erich Schubert, and Arthur Zimek (2012). Evaluation of Clusterings - Metrics and Visual Support. ICDE, 1285-1288, IEEE, 10.1109/ICDE.2012.128, BibTeX
  13. Hans-Peter Kriegel, Peer Kröger, Erich Schubert, and Arthur Zimek (2012). Outlier Detection in Arbitrarily Oriented Subspaces. ICDM, 379-388, IEEE, 10.1109/ICDM.2012.21, BibTeX
  14. Mohamed Bouguessa (2012). A Probabilistic Combination Approach to Improve Outlier Detection. ICTAI, 666-673, IEEE, 10.1109/ICTAI.2012.95, BibTeX
  15. Monalisa Mandal, and Anirban Mukhopadhyay (2012). Identifying most relevant non-redundant gene markers from gene expression data using PSO-based graph -theoretic approach. 2012 2nd IEEE International Conference on Parallel, Distributed and Grid Computing, 374-379, IEEE, 10.1109/PDGC.2012.6449849
  16. Erich Schubert, Remigius Wojdanowski, Arthur Zimek, and Hans-Peter Kriegel (2012). On Evaluation of Outlier Rankings and Outlier Scores. SDM, 1047-1058, SIAM / Omnipress, 10.1137/1.9781611972825.90, BibTeX
  17. Thomas Bernecker, Franz Graf, Hans-Peter Kriegel, Nepomuk Seiler, Christoph Türmer, and Dieter Dill (2012). Knowing: a generic data analysis application. EDBT, 630-633, ACM, 10.1145/2247596.2247683, BibTeX
  18. Stephan Günnemann, Ines Färber, Kittipat Virochsiri, and Thomas Seidl (2012). Subspace correlation clustering: finding locally correlated dimensions in subspace projections of the data. KDD, 352-360, ACM, 10.1145/2339530.2339588, BibTeX
  19. Linda Dib, and Alessandra Carbone (2012). CLAG: an unsupervised non hierarchical clustering algorithm handling biological data. BMC Bioinform. 13, 194, 10.1186/1471-2105-13-194, BibTeX
  20. Thomas Bernecker (2012). Similarity processing in multi-observation data. 1-253, Ludwig Maximilian University of Munich, Germany, BibTeX
  21. Jens Ehlers (2012). Self-adaptive performance monitoring for component-based software systems. 1-232, University of Kiel, BibTeX
  22. Franz Graf (2012). Data and knowledge engineering for medical image and sensor data. 1-221, Ludwig Maximilian University of Munich, Germany, BibTeX
  23. Stephan Günnemann (2012). Subspace clustering for complex data. RWTH Aachen University, BibTeX
  24. Steffen Suchandt, and Hartmut Runge (2012). Along-track interferometry using TanDEM-X: First results from marine and land applications. EUSAR 2012; 9th European Conference on Synthetic Aperture Radar, 392-395, VDE, 978-3-8007-3404-7
  25. Arthur Zimek (2012). There and Back Again Outlier Detection between Statistical Reasoning and Efficient Database Methods.
  26. Bruno Tavares (2012). Sistema de recomendação para plataformas de e-learning. Instituto Politécnico do Porto. Instituto Superior de Engenharia do Porto
  27. E. B. Beuschau (2012). Learning usage behavior based on app feedback.
  28. Francesco Indaco (2012). Hierarchical Clustering Using Level Sets. San Jose State University
  29. Ilango Velchamy, R Subramanian, and V Vasudevan (2012). A Five Step Procedure for Outlier Analysis in Data Mining. European Journal of Scientific Research
  30. Γρηγόριος Αθανασίου (2012). Business plan νέας ηλεκτρονικής επιχείρησης (Δημιουργία-Εφαρμογή). Πανεπιστήμιο Μακεδονίας Οικονομικών και Κοινωνικών Επιστημών
  31. Νικόλαος Δ. Γρίβας, and Nikolaos D. Grivas (2012). Υπολογισμός ισοχρονικών καμπύλων χρονοαπόστασης σε οδικά δίκτυα (Isochrone computation on road networks).

2011

  1. Hans-Peter Kriegel, Peer Kröger, Jörg Sander, and Arthur Zimek (2011). Density-based clustering. WIREs Data Mining Knowl. Discov. 1(3), 231-240, 10.1002/widm.30, BibTeX
  2. Thomas Bernecker, Michael E. Houle, Hans-Peter Kriegel, Peer Kröger, Matthias Renz, Erich Schubert, and Arthur Zimek (2011). Quality of Similarity Rankings in Time Series. SSTD, 422-440, Springer, 10.1007/978-3-642-22922-0_25, BibTeX
  3. Elke Achtert, Ahmed Hettab, Hans-Peter Kriegel, Erich Schubert, and Arthur Zimek (2011). Spatial Outlier Detection: Data, Algorithms, Visualizations. SSTD, 512-516, Springer, 10.1007/978-3-642-22922-0_41, BibTeX
  4. Yong Shi, and Li Zhang (2011). COID: A cluster-outlier iterative detection approach to multi-dimensional data analysis. Knowl. Inf. Syst. 28(3), 709-733, 10.1007/s10115-010-0323-y, BibTeX
  5. Kai Ming Ting, Takashi Washio, Jonathan R. Wells, and Fei Tony Liu (2011). Density Estimation Based on Mass. ICDM, 715-724, IEEE, 10.1109/ICDM.2011.47, BibTeX
  6. Hans-Peter Kriegel, Peer Kröger, Erich Schubert, and Arthur Zimek (2011). Interpreting and Unifying Outlier Scores. SDM, 13-24, SIAM / Omnipress, 10.1137/1.9781611972818.2, BibTeX
  7. Claudia Plant (2011). SONAR: Signal De-mixing for Robust Correlation Clustering. SDM, 319-330, SIAM / Omnipress, 10.1137/1.9781611972818.28, BibTeX
  8. Anca Maria Ivanescu, Thivaharan Albin, Dirk Abel, and Thomas Seidl (2011). Employing correlation clustering for the identification of piecewise affine models. Proceedings of the 2011 workshop on Knowledge discovery, modeling and simulation - KDMS ‘11, ACM Press, 10.1145/2023568.2023575
  9. Stephan Günnemann, Hardy Kremer, and Thomas Seidl (2011). An extension of the PMML standard to subspace clustering models. Proceedings of the 2011 workshop on Predictive markup language modeling - PMML ‘11, ACM Press, 10.1145/2023598.2023605
  10. Resat Selbas, Arzu Sencan, and Ecir U. (2011). Data Mining Method For Energy System Aplications. Knowledge-Oriented Applications in Data Mining, InTech, 10.5772/13710
  11. Emmanuel Müller, Ira Assent, Stephan Günnemann, Patrick Gerwert, Matthias Hannen, Timm Jansen, and Thomas Seidl (2011). A Framework for Evaluation and Exploration of Clustering Algorithms in Subspaces of High Dimensional Databases. BTW, 347-366, GI, BibTeX
  12. Hans-Peter Kriegel, Erich Schubert, and Arthur Zimek (2011). Evaluation of Multiple Clustering Solutions. MultiClust@ECML/PKDD, 55-66, CEUR-WS.org, BibTeX
  13. Johan Mazel (2011). Unsupervised network anomaly detection. (Détection non supervisée d’anomalies dans les réseaux de communication). INSA Toulouse, France, BibTeX
  14. Bilkis Jamal Ferdosi (2011). Scalable analysis and visualization of high-dimensional astronomical data sets. s.n. 9789036749633
  15. Iliya Mitov (2011). Class association rule mining using multidimensional numbered information spaces.
  16. Ευλάμπιος Αποστολίδης (2011). Συγκριτική μελέτη μεθόδων κατασκευής του R* TREE με όρους αποδοτικότητας για ερωτήματα κοντινότερου γείτονα σε πολυδιάστατους χώρους δεδομένων. Πανεπιστήμιο Μακεδονίας Οικονομικών και Κοινωνικών Επιστημών

2010

  1. Elke Achtert, Hans-Peter Kriegel, Lisa Reichert, Erich Schubert, Remigius Wojdanowski, and Arthur Zimek (2010). Visual Evaluation of Outlier Detection Models. DASFAA (2), 396-399, Springer, 10.1007/978-3-642-12098-5_34, BibTeX
  2. Dominik Benz, Andreas Hotho, Robert Jäschke, Beate Krause, Folke Mitzlaff, Christoph Schmitz, and Gerd Stumme (2010). The social bookmark and publication management system bibsonomy - A platform for evaluating and demonstrating Web 2.0 research. VLDB J. 19(6), 849-875, 10.1007/s00778-010-0208-4, BibTeX
  3. Arik Messerman, Tarik Mustafic, Seyit Ahmet Çamtepe, and Sahin Albayrak (2010). A generic framework and runtime environment for development and evaluation of behavioral biometrics solutions. ISDA, 136-141, IEEE, 10.1109/ISDA.2010.5687276, BibTeX
  4. Bilkis J. Ferdosi, Hugo Buddelmeijer, Scott C. Trager, Michael H. F. Wilkinson, and Jos B. T. M. Roerdink (2010). Finding and visualizing relevant subspaces for clustering high-dimensional astronomical data using connected morphological operators. IEEE VAST, 35-42, IEEE, 10.1109/VAST.2010.5652450, BibTeX
  5. Tobias Emrich, Hans-Peter Kriegel, Peer Kröger, Matthias Renz, and Andreas Züfle (2010). Boosting spatial pruning: on optimal pruning of MBRs. SIGMOD Conference, 39-50, ACM, 10.1145/1807167.1807174, BibTeX
  6. Kai Ming Ting, Guang-Tong Zhou, Fei Tony Liu, and James Swee Chuan Tan (2010). Mass estimation and its applications. KDD, 989-998, ACM, 10.1145/1835804.1835929, BibTeX
  7. Tobias Emrich, Franz Graf, Hans-Peter Kriegel, Matthias Schubert, and Marisa Thoma (2010). On the impact of flash SSDs on spatial indexing. DaMoN, 3-8, ACM, 10.1145/1869389.1869390, BibTeX
  8. Emmanuel Alexander Müller (2010). Efficient knowledge discovery in subspaces of high dimensional databases. 1-270, RWTH Aachen University, BibTeX
  9. Albert Hein, and Thomas Kirste (2010). Unsupervised detection of motion primitives in very high dimensional sensor data. BMI, 22-37, CEUR-WS.org

2009

  1. Hans-Peter Kriegel, Peer Kröger, Erich Schubert, and Arthur Zimek (2009). Outlier Detection in Axis-Parallel Subspaces of High Dimensional Data. PAKDD, 831-838, Springer, 10.1007/978-3-642-01307-2_86, BibTeX
  2. Elke Achtert, Thomas Bernecker, Hans-Peter Kriegel, Erich Schubert, and Arthur Zimek (2009). ELKI in Time: ELKI 0.2 for the Performance Evaluation of Distance Measures for Time Series. SSTD, 436-440, Springer, 10.1007/978-3-642-02982-0_35, BibTeX
  3. Gabriela Moise, Arthur Zimek, Peer Kröger, Hans-Peter Kriegel, and Jörg Sander (2009). Subspace and projected clustering: experimental evaluation and analysis. Knowl. Inf. Syst. 21(3), 299-326, 10.1007/s10115-009-0226-y, BibTeX
  4. Hans-Peter Kriegel, Peer Kröger, and Arthur Zimek (2009). Clustering high-dimensional data: A survey on subspace clustering, pattern-based clustering, and correlation clustering. ACM Trans. Knowl. Discov. Data 3(1), 1:1-1:58, 10.1145/1497577.1497578, BibTeX
  5. Hans-Peter Kriegel, Peer Kröger, Erich Schubert, and Arthur Zimek (2009). LoOP: local outlier probabilities. CIKM, 1649-1652, ACM, 10.1145/1645953.1646195, BibTeX
  6. Arthur Zimek (2009). Correlation clustering. SIGKDD Explor. 11(1), 53-54, 10.1145/1656274.1656286, BibTeX

2008

  1. Elke Achtert, Hans-Peter Kriegel, and Arthur Zimek (2008). ELKI: A Software System for Evaluation of Subspace Clustering Algorithms. SSDBM, 580-585, Springer, 10.1007/978-3-540-69497-7_41, BibTeX
  2. Hans-Peter Kriegel, Peer Kröger, and Arthur Zimek (2008). Detecting clusters in moderate-to-high dimensional data: subspace clustering, pattern-based clustering, and correlation clustering. Proc. VLDB Endow. 1(2), 1528-1529, 10.14778/1454159.1454223, BibTeX

Finding more

Papers that cite ELKI releases can be found:

Release 0.1: Semantic Scholar Google Scholar OpenCitations Microsoft Academic OpenAlex

Release 0.2: Semantic Scholar Google Scholar OpenCitations Microsoft Academic OpenAlex

Release 0.3: Semantic Scholar Google Scholar OpenCitations Microsoft Academic OpenAlex

Release 0.4: Semantic Scholar Google Scholar OpenCitations Microsoft Academic OpenAlex

Release 0.5: Semantic Scholar Google Scholar OpenCitations Microsoft Academic OpenAlex

Release 0.6: Semantic Scholar Google Scholar OpenCitations Microsoft Academic OpenAlex

Release 0.7: Semantic Scholar Google Scholar OpenCitations Microsoft Academic OpenAlex

Release 0.7.5: Semantic Scholar Google Scholar OpenCitations:n/a Microsoft Academic OpenAlex

Release 0.8: Semantic Scholar Google Scholar OpenCitations OpenAlex