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SIGMOD
2004
ACM
144views Database» more  SIGMOD 2004»
14 years 7 months ago
Information-Theoretic Tools for Mining Database Structure from Large Data Sets
Periklis Andritsos, Renée J. Miller, Panayi...
KDD
2002
ACM
138views Data Mining» more  KDD 2002»
14 years 8 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
KDD
2001
ACM
253views Data Mining» more  KDD 2001»
14 years 8 months ago
GESS: a scalable similarity-join algorithm for mining large data sets in high dimensional spaces
The similarity join is an important operation for mining high-dimensional feature spaces. Given two data sets, the similarity join computes all tuples (x, y) that are within a dis...
Jens-Peter Dittrich, Bernhard Seeger
SIGMOD
2000
ACM
173views Database» more  SIGMOD 2000»
13 years 11 months ago
Efficient Algorithms for Mining Outliers from Large Data Sets
In this paper, we propose a novel formulation for distance-based outliers that is based on the distance of a point from its kth nearest neighbor. We rank each point on the basis o...
Sridhar Ramaswamy, Rajeev Rastogi, Kyuseok Shim
IDEAL
2004
Springer
14 years 1 months ago
Mining Large Engineering Data Sets on the Grid Using AURA
AURA (Advanced Uncertain Reasoning Architecture) is a parallel pattern matching technology intended for high-speed approximate search and match operations on large unstructured dat...
Bojian Liang, Jim Austin