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Open Knowledge
XHTML 1.0 W3C Rec
CSS 2.1 W3C CanRec
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Travelled to:
1 × Canada
1 × France
1 × Norway
2 × Germany
8 × USA
Collaborated with:
H.Kriegel M.Ester X.Xu M.A.Nascimento G.Moise J.Zhou M.M.Breunig A.Coman S.Nassar C.Cheng A.Zimek M.Gaudet R.J.G.B.Campello M.Fokaefs N.Tsantalis A.Chatzigeorgiou S.Rasetic J.Elding R.T.Ng M.Ankerst A.Frommelt M.Wimmer
Talks about:
cluster (7) data (5) spatial (3) densiti (3) databas (3) effici (3) detect (3) increment (2) algorithm (2) identifi (2)

Person: Jörg Sander

DBLP DBLP: Sander:J=ouml=rg

Contributed to:

KDD 20132013
ICSM 20092009
KDD 20082008
CIKM 20052005
VLDB 20052005
SIGMOD 20042004
VLDB 20032003
SIGMOD 20002000
SIGMOD 19991999
KDD 19981998
VLDB 19981998
KDD 19971997
KDD 19961996

Wrote 13 papers:

KDD-2013-ZimekGCS #detection #effectiveness #performance
Subsampling for efficient and effective unsupervised outlier detection ensembles (AZ, MG, RJGBC, JS), pp. 428–436.
ICSM-2009-FokaefsTCS #clustering #object-oriented #using
Decomposing object-oriented class modules using an agglomerative clustering technique (MF, NT, AC, JS), pp. 93–101.
KDD-2008-MoiseS #approach #clustering #novel #statistics
Finding non-redundant, statistically significant regions in high dimensional data: a novel approach to projected and subspace clustering (GM, JS), pp. 533–541.
CIKM-2005-ComanNS #energy #network #performance #query
Exploiting redundancy in sensor networks for energy efficient processing of spatiotemporal region queries (AC, MAN, JS), pp. 187–194.
VLDB-2005-RaseticSEN #performance
A Trajectory Splitting Model for Efficient Spatio-Temporal Indexing (SR, JS, JE, MAN), pp. 934–945.
SIGMOD-2004-NassarSC #clustering #effectiveness #incremental #summary
Incremental and Effective Data Summarization for Dynamic Hierarchical Clustering (SN, JS, CC), pp. 467–478.
VLDB-2003-ZhouS #clustering #metric
Data Bubbles for Non-Vector Data: Speeding-up Hierarchical Clustering in Arbitrary Metric Spaces (JZ, JS), pp. 452–463.
SIGMOD-2000-BreunigKNS #identification #named
LOF: Identifying Density-Based Local Outliers (MMB, HPK, RTN, JS), pp. 93–104.
SIGMOD-1999-AnkerstBKS #clustering #identification #named
OPTICS: Ordering Points To Identify the Clustering Structure (MA, MMB, HPK, JS), pp. 49–60.
KDD-1998-EsterFKS #algorithm #database #detection
Algorithms for Characterization and Trend Detection in Spatial Databases (ME, AF, HPK, JS), pp. 44–50.
VLDB-1998-EsterKSWX #clustering #incremental #mining
Incremental Clustering for Mining in a Data Warehousing Environment (ME, HPK, JS, MW, XX), pp. 323–333.
KDD-1997-EsterKSX #database #detection #set
Density-Connected Sets and their Application for Trend Detection in Spatial Databases (ME, HPK, JS, XX), pp. 10–15.
KDD-1996-EsterKSX #algorithm #clustering #database #scalability
A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise (ME, HPK, JS, XX), pp. 226–231.

Bibliography of Software Language Engineering in Generated Hypertext (BibSLEIGH) is created and maintained by Dr. Vadim Zaytsev.
Hosted as a part of SLEBOK on GitHub.