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SIGMOD
2004
ACM
144views Database» more  SIGMOD 2004»
15 years 9 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»
15 years 9 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»
15 years 9 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»
15 years 1 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
15 years 2 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