| On the evaluation of unsupervised outlier detection: measures, datasets, and an empirical study GO Campos, A Zimek, J Sander, RJGB Campello, B Micenková, ... Data mining and knowledge discovery 30, 891-927, 2016 | 799 | 2016 |
| Evaluating clustering in subspace projections of high dimensional data E Müller, S Günnemann, I Assent, T Seidl Proceedings of the VLDB Endowment 2 (1), 1270-1281, 2009 | 363 | 2009 |
| The clustree: indexing micro-clusters for anytime stream mining P Kranen, I Assent, C Baldauf, T Seidl Knowledge and information systems 29, 249-272, 2011 | 343 | 2011 |
| Clustering high dimensional data I Assent Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 2 (4 …, 2012 | 192 | 2012 |
| DUSC: Dimensionality unbiased subspace clustering I Assent, R Krieger, E Müller, T Seidl seventh IEEE international conference on data mining (ICDM 2007), 409-414, 2007 | 168 | 2007 |
| Explaining outliers by subspace separability B Micenková, RT Ng, XH Dang, I Assent 2013 IEEE 13th international conference on data mining, 518-527, 2013 | 144 | 2013 |
| Clicks: An effective algorithm for mining subspace clusters in categorical datasets MJ Zaki, M Peters, I Assent, T Seidl Proceedings of the eleventh ACM SIGKDD international conference on Knowledge …, 2005 | 140 | 2005 |
| Anyout: Anytime outlier detection on streaming data I Assent, P Kranen, C Baldauf, T Seidl Database Systems for Advanced Applications: 17th International Conference …, 2012 | 132 | 2012 |
| INSCY: Indexing subspace clusters with in-process-removal of redundancy I Assent, R Krieger, E Müller, T Seidl 2008 Eighth IEEE International Conference on Data Mining, 719-724, 2008 | 132 | 2008 |
| Discriminative features for identifying and interpreting outliers XH Dang, I Assent, RT Ng, A Zimek, E Schubert 2014 IEEE 30th international conference on data engineering, 88-99, 2014 | 115 | 2014 |
| The TS-tree: efficient time series search and retrieval I Assent, R Krieger, F Afschari, T Seidl Proceedings of the 11th international conference on Extending database …, 2008 | 106 | 2008 |
| Outlier ranking via subspace analysis in multiple views of the data E Müller, I Assent, P Iglesias, Y Mülle, K Böhm 2012 IEEE 12th international conference on data mining, 529-538, 2012 | 103 | 2012 |
| Relevant subspace clustering: Mining the most interesting non-redundant concepts in high dimensional data E Müller, I Assent, S Günnemann, R Krieger, T Seidl 2009 Ninth IEEE International Conference on Data Mining, 377-386, 2009 | 97 | 2009 |
| Outsourced similarity search on metric data assets ML Yiu, I Assent, CS Jensen, P Kalnis IEEE Transactions on knowledge and data engineering 24 (2), 338-352, 2010 | 96 | 2010 |
| OutRank: ranking outliers in high dimensional data E Muller, I Assent, U Steinhausen, T Seidl 2008 IEEE 24th international conference on data engineering workshop, 600-603, 2008 | 94 | 2008 |
| Approximation techniques for indexing the earth mover's distance in multimedia databases I Assent, A Wenning, T Seidl 22nd International Conference on Data Engineering (ICDE'06), 11-11, 2006 | 94 | 2006 |
| Self-adaptive anytime stream clustering P Kranen, I Assent, C Baldauf, T Seidl 2009 Ninth IEEE International Conference on Data Mining, 249-258, 2009 | 91 | 2009 |
| Anticipatory DTW for efficient similarity search in time series databases I Assent, M Wichterich, R Krieger, H Kremer, T Seidl Proceedings of the VLDB Endowment 2 (1), 826-837, 2009 | 89 | 2009 |
| VISA: visual subspace clustering analysis I Assent, R Krieger, E Müller, T Seidl ACM SIGKDD Explorations Newsletter 9 (2), 5-12, 2007 | 85 | 2007 |
| Local outlier detection with interpretation XH Dang, B Micenková, I Assent, RT Ng Machine Learning and Knowledge Discovery in Databases: European Conference …, 2013 | 84 | 2013 |
Thomas SeidlProfessor of Computer Science, Ludwig-Maximilians-Universität München (LMU Munich), MCML, Germany在 dbs.ifi.lmu.de 的电子邮件经过验证
