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KDD
2006
ACM
147views Data Mining» more  KDD 2006»
16 years 7 months ago
Summarizing itemset patterns using probabilistic models
In this paper, we propose a novel probabilistic approach to summarize frequent itemset patterns. Such techniques are useful for summarization, post-processing, and end-user interp...
Chao Wang, Srinivasan Parthasarathy
KDD
2004
ACM
158views Data Mining» more  KDD 2004»
16 years 7 months ago
A generalized maximum entropy approach to bregman co-clustering and matrix approximation
Co-clustering is a powerful data mining technique with varied applications such as text clustering, microarray analysis and recommender systems. Recently, an informationtheoretic ...
Arindam Banerjee, Inderjit S. Dhillon, Joydeep Gho...
KDD
2004
ACM
150views Data Mining» more  KDD 2004»
16 years 7 months ago
Markov Blankets and Meta-heuristics Search: Sentiment Extraction from Unstructured Texts
Extracting sentiments from unstructured text has emerged as an important problem in many disciplines. An accurate method would enable us, for example, to mine online opinions from ...
Edoardo Airoldi, Xue Bai, Rema Padman
KDD
2002
ACM
166views Data Mining» more  KDD 2002»
16 years 7 months ago
Frequent term-based text clustering
Text clustering methods can be used to structure large sets of text or hypertext documents. The well-known methods of text clustering, however, do not really address the special p...
Florian Beil, Martin Ester, Xiaowei Xu
KDD
2002
ACM
125views Data Mining» more  KDD 2002»
16 years 7 months ago
Pattern discovery in sequences under a Markov assumption
In this paper we investigate the general problem of discovering recurrent patterns that are embedded in categorical sequences. An important real-world problem of this nature is mo...
Darya Chudova, Padhraic Smyth