Jörg Sander
Jörg Sander
Professor, Computing Science, University of Alberta
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Cited by
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A density-based algorithm for discovering clusters in large spatial databases with noise
M Ester, HP Kriegel, J Sander, X Xu
kdd 96 (34), 226-231, 1996
LOF: identifying density-based local outliers
MM Breunig, HP Kriegel, RT Ng, J Sander
Proceedings of the 2000 ACM SIGMOD international conference on Management of …, 2000
OPTICS: Ordering points to identify the clustering structure
M Ankerst, MM Breunig, HP Kriegel, J Sander
ACM Sigmod record 28 (2), 49-60, 1999
DBSCAN revisited, revisited: why and how you should (still) use DBSCAN
E Schubert, J Sander, M Ester, HP Kriegel, X Xu
ACM Transactions on Database Systems (TODS) 42 (3), 1-21, 2017
Density-based clustering based on hierarchical density estimates
RJGB Campello, D Moulavi, J Sander
Pacific-Asia conference on knowledge discovery and data mining, 160-172, 2013
Density-based clustering in spatial databases: The algorithm gdbscan and its applications
J Sander, M Ester, HP Kriegel, X Xu
Data mining and knowledge discovery 2, 169-194, 1998
Density‐based clustering
HP Kriegel, P Kröger, J Sander, A Zimek
Wiley interdisciplinary reviews: data mining and knowledge discovery 1 (3 …, 2011
Incremental generalization for mining in a data warehousing environment
M Ester, R Wittmann
Advances in Database Technology—EDBT'98: 6th International Conference on …, 1998
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
Hierarchical density estimates for data clustering, visualization, and outlier detection
RJGB Campello, D Moulavi, A Zimek, J Sander
ACM Transactions on Knowledge Discovery from Data (TKDD) 10 (1), 1-51, 2015
A distribution-based clustering algorithm for mining in large spatial databases
X Xu, M Ester, HP Kriegel, J Sander
Proceedings 14th International Conference on Data Engineering, 324-331, 1998
Spatial data mining: A database approach
M Ester, HP Kriegel, J Sander
Advances in Spatial Databases: 5th International Symposium, SSD'97 Berlin …, 1997
Knowledge discovery in databases: Techniken und Anwendungen
M Ester, J Sander
Springer-Verlag, 2013
Proceedings of the Second International Conference on Knowledge Discovery and Data Mining. KDD’96
M Ester, HP Kriegel, J Sander, X Xu, E Simoudis, J Han, U Fayyad
A density‐based algorithm for discovering clusters in large spatial …, 1996
Ensembles for unsupervised outlier detection: challenges and research questions a position paper
A Zimek, RJGB Campello, J Sander
Acm Sigkdd Explorations Newsletter 15 (1), 11-22, 2014
Optics-of: Identifying local outliers
MM Breunig, HP Kriegel, RT Ng, J Sander
Principles of Data Mining and Knowledge Discovery: Third European Conference …, 1999
Independent quantization: An index compression technique for high-dimensional data spaces
S Berchtold, C Bohm, HV Jagadish, HP Kriegel, J Sander
Proceedings of 16th International Conference on Data Engineering (Cat. No …, 2000
Density-based clustering validation
D Moulavi, PA Jaskowiak, RJGB Campello, A Zimek, J Sander
Proceedings of the 2014 SIAM international conference on data mining, 839-847, 2014
Subsampling for efficient and effective unsupervised outlier detection ensembles
A Zimek, M Gaudet, RJGB Campello, J Sander
Proceedings of the 19th ACM SIGKDD international conference on Knowledge …, 2013
Spatial data mining: database primitives, algorithms and efficient DBMS support
M Ester, A Frommelt, HP Kriegel, J Sander
Data Mining and Knowledge Discovery 4, 193-216, 2000
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