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KDD
2002
ACM
138views Data Mining» more  KDD 2002»
16 years 5 months ago
Learning to match and cluster large high-dimensional data sets for data integration
Part of the process of data integration is determining which sets of identifiers refer to the same real-world entities. In integrating databases found on the Web or obtained by us...
William W. Cohen, Jacob Richman
SIGMOD
2008
ACM
107views Database» more  SIGMOD 2008»
16 years 5 months ago
Outlier-robust clustering using independent components
How can we efficiently find a clustering, i.e. a concise description of the cluster structure, of a given data set which contains an unknown number of clusters of different shape ...
Christian Böhm, Christos Faloutsos, Claudia P...
142
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CIDM
2009
IEEE
15 years 9 months ago
An architecture and algorithms for multi-run clustering
—This paper addresses two main challenges for clustering which require extensive human effort: selecting appropriate parameters for an arbitrary clustering algorithm and identify...
Rachsuda Jiamthapthaksin, Christoph F. Eick, Vadee...
ASIAN
2005
Springer
150views Algorithms» more  ASIAN 2005»
15 years 10 months ago
ACB-R: An Adaptive Clustering-Based Data Replication Algorithm on a P2P Data-Store
Replication on geographically distributed, unreliable, P2P interconnecting nodes can offer high data availability and low network latency for replica access. The challenge is how ...
Junhu Zhang, Dongqing Yang, Shiwei Tang
NIPS
2007
15 years 6 months ago
DIFFRAC: a discriminative and flexible framework for clustering
We present a novel linear clustering framework (DIFFRAC) which relies on a linear discriminative cost function and a convex relaxation of a combinatorial optimization problem. The...
Francis Bach, Zaïd Harchaoui