Information-Theoretic Co-Clustering

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Information-Theoretic Co-Clustering (2003)

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by Inderjit S. Dhillon , Subramanyam Mallela , Dharmendra S. Modha

Venue:	In KDD
Citations:	345 - 12 self

BibTeX

@INPROCEEDINGS{Dhillon03information-theoreticco-clustering,
    author = {Inderjit S. Dhillon and Subramanyam Mallela and Dharmendra S. Modha},
    title = {Information-Theoretic Co-Clustering},
    booktitle = {In KDD},
    year = {2003},
    pages = {89--98},
    publisher = {ACM Press}
}

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Abstract

Two-dimensional contingency or co-occurrence tables arise frequently in important applications such as text, web-log and market-basket data analysis. A basic problem in contingency table analysis is co-clustering: simultaneous clustering of the rows and columns. A novel theoretical formulation views the contingency table as an empirical joint probability distribution of two discrete random variables and poses the co-clustering problem as an optimization problem in information theory -- the optimal co-clustering maximizes the mutual information between the clustered random variables subject to constraints on the number of row and column clusters.

Keyphrases

information-theoretic co-clustering contingency table empirical joint probability distribution discrete random variable clustered random variable mutual information basic problem column cluster two-dimensional contingency information theory simultaneous clustering optimization problem novel theoretical formulation co-occurrence table co-clustering problem optimal co-clustering contingency table analysis market-basket data analysis important application

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