Jörg Sander
Jörg Sander
Professor, Computing Science, University of Alberta
Dirección de correo verificada de ualberta.ca
TítuloCitado porAño
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
169221996
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
48162000
OPTICS: ordering points to identify the clustering structure
M Ankerst, MM Breunig, HP Kriegel, J Sander
ACM Sigmod record 28 (2), 49-60, 1999
38781999
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 (2), 169-194, 1998
13791998
Incremental generalization for mining in a data warehousing environment
M Ester, R Wittmann
International Conference on Extending Database Technology, 135-149, 1998
6881998
Density‐based clustering
HP Kriegel, P Kröger, J Sander, A Zimek
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 1 (3 …, 2011
5402011
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
4282013
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
4141998
Spatial data mining: A database approach
M Ester, HP Kriegel, J Sander
International Symposium on Spatial Databases, 47-66, 1997
3981997
Knowledge discovery in databases: Techniken und Anwendungen
M Ester, J Sander
Springer-Verlag, 2013
2722013
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
2702000
Optics-of: Identifying local outliers
MM Breunig, HP Kriegel, RT Ng, J Sander
European Conference on Principles of Data Mining and Knowledge Discovery …, 1999
2591999
proceedings of the second international conference on knowledge discovery and data mining
M Ester, HP Kriegel, J Sander, X Xu
AAAI press, 1996
240*1996
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 (4), 891-927, 2016
2332016
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
2272015
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
2142017
Spatial data mining: database primitives, algorithms and efficient DBMS support
M Ester, A Frommelt, HP Kriegel, J Sander
Data Mining and Knowledge Discovery 4 (2-3), 193-216, 2000
2072000
Segmenting brain tumors with conditional random fields and support vector machines
CH Lee, M Schmidt, A Murtha, A Bistritz, J Sander, R Greiner
International Workshop on Computer Vision for Biomedical Image Applications …, 2005
1762005
Algorithms for Characterization and Trend Detection in Spatial Databases.
M Ester, A Frommelt, HP Kriegel, J Sander
KDD, 44-50, 1998
1741998
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
1712014
El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.
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