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» Document clustering using nonnegative matrix factorization
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105
Voted
SIGIR
2005
ACM
15 years 7 months ago
Relation between PLSA and NMF and implications
Non-negative Matrix Factorization (NMF, [5]) and Probabilistic Latent Semantic Analysis (PLSA, [4]) have been successfully applied to a number of text analysis tasks such as docum...
Éric Gaussier, Cyril Goutte
CIKM
2008
Springer
15 years 3 months ago
Integrating clustering and multi-document summarization to improve document understanding
Document understanding techniques such as document clustering and multi-document summarization have been receiving much attention in recent years. Current document clustering meth...
Dingding Wang, Shenghuo Zhu, Tao Li, Yun Chi, Yiho...
148
Voted
ICASSP
2009
IEEE
14 years 11 months ago
Weighted nonnegative matrix factorization
Nonnegative matrix factorization (NMF) is a widely-used method for low-rank approximation (LRA) of a nonnegative matrix (matrix with only nonnegative entries), where nonnegativity...
Yong-Deok Kim, Seungjin Choi
SIGIR
2004
ACM
15 years 7 months ago
GaP: a factor model for discrete data
We present a probabilistic model for a document corpus that combines many of the desirable features of previous models. The model is called “GaP” for Gamma-Poisson, the distri...
John F. Canny