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KDD
2003
ACM
120views Data Mining» more  KDD 2003»
16 years 7 months ago
On detecting differences between groups
Understanding the differences between contrasting groups is a fundamental task in data analysis. This realization has led to the development of a new special purpose data mining t...
Geoffrey I. Webb, Shane M. Butler, Douglas A. Newl...
KDD
2003
ACM
135views Data Mining» more  KDD 2003»
16 years 7 months ago
Efficiently handling feature redundancy in high-dimensional data
High-dimensional data poses a severe challenge for data mining. Feature selection is a frequently used technique in preprocessing high-dimensional data for successful data mining....
Lei Yu, Huan Liu
KDD
2002
ACM
136views Data Mining» more  KDD 2002»
16 years 7 months ago
Relational Markov models and their application to adaptive web navigation
Relational Markov models (RMMs) are a generalization of Markov models where states can be of different types, with each type described by a different set of variables. The domain ...
Corin R. Anderson, Pedro Domingos, Daniel S. Weld
KDD
2002
ACM
171views Data Mining» more  KDD 2002»
16 years 7 months ago
Mining complex models from arbitrarily large databases in constant time
In this paper we propose a scaling-up method that is applicable to essentially any induction algorithm based on discrete search. The result of applying the method to an algorithm ...
Geoff Hulten, Pedro Domingos
KDD
2001
ACM
166views Data Mining» more  KDD 2001»
16 years 7 months ago
Generalized clustering, supervised learning, and data assignment
Clustering algorithms have become increasingly important in handling and analyzing data. Considerable work has been done in devising effective but increasingly specific clustering...
Annaka Kalton, Pat Langley, Kiri Wagstaff, Jungsoo...
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