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WEBI
2007
Springer
14 years 5 months ago
Pairwise Constraints-Guided Non-negative Matrix Factorization for Document Clustering
Nonnegative Matrix Factorization (NMF) has been proven to be effective in text mining. However, since NMF is a well-known unsupervised components analysis technique, the existing ...
Yujiu Yang, Bao-Gang Hu
MLDM
2005
Springer
14 years 4 months ago
CorePhrase: Keyphrase Extraction for Document Clustering
Abstract. The ability to discover the topic of a large set of text documents using relevant keyphrases is usually regarded as a very tedious task if done by hand. Automatic keyphra...
Khaled M. Hammouda, Diego N. Matute, Mohamed S. Ka...
ICDM
2007
IEEE
129views Data Mining» more  ICDM 2007»
14 years 5 months ago
Semi-supervised Clustering Using Bayesian Regularization
Text clustering is most commonly treated as a fully automated task without user supervision. However, we can improve clustering performance using supervision in the form of pairwi...
Zuobing Xu, Ram Akella, Mike Ching, Renjie Tang
ECML
2001
Springer
14 years 3 months ago
Iterative Double Clustering for Unsupervised and Semi-supervised Learning
We present a powerful meta-clustering technique called Iterative Double Clustering (IDC). The IDC method is a natural extension of the recent Double Clustering (DC) method of Slon...
Ran El-Yaniv, Oren Souroujon
SIGIR
2002
ACM
13 years 10 months ago
Generic summarization and keyphrase extraction using mutual reinforcement principle and sentence clustering
A novel method for simultaneous keyphrase extraction and generic text summarization is proposed by modeling text documents as weighted undirected and weighted bipartite graphs. Sp...
Hongyuan Zha