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Ira Assent
Ira Assent
Professor of Computer Science, Aarhus University, Denmark; IAS-8, Forschungszentrum Jülich
Zweryfikowany adres z cs.au.dk
Tytuł
Cytowane przez
Cytowane przez
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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
8982016
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
3672009
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
3562011
Advances in Spatial and Temporal Databases: 11th International Symposium, SSTD 2009 Aalborg, Denmark, July 8-10, 2009 Proceedings
N Mamoulis, T Seidl, TB Pedersen, K Torp, I Assent
Lecture Notes in Computer Science 5644, 2009
237*2009
Clustering high dimensional data
I Assent
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 2 (4 …, 2012
2232012
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
1692007
Explaining outliers by subspace separability
B Micenková, RT Ng, XH Dang, I Assent
2013 IEEE 13th international conference on data mining, 518-527, 2013
1552013
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
1442005
Anyout: Anytime outlier detection on streaming data
I Assent, P Kranen, C Baldauf, T Seidl
Database Systems for Advanced Applications: 17th International Conference …, 2012
1372012
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
1322008
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
1192014
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
1072012
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
1072008
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
982009
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
972008
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
962009
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
942010
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
942006
Self-adaptive anytime stream clustering
P Kranen, I Assent, C Baldauf, T Seidl
2009 Ninth IEEE International Conference on Data Mining, 249-258, 2009
922009
Local outlier detection with interpretation
XH Dang, B Micenková, I Assent, RT Ng
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2013
872013
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