A Probabilistic Sentence Reduction Using Maximum Entropy Model

Minh LE NGUYEN  Masaru FUKUSHI  Susumu HORIGUCHI  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E88-D   No.2   pp.278-288
Publication Date: 2005/02/01
Online ISSN: 
Print ISSN: 0916-8532
Type of Manuscript: PAPER
Category: Natural Language Processing
Keyword: 
sentence reduction,  text summarization,  natural language processing,  maximum entropy models,  

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Summary: 
This paper describes a new probabilistic sentence reduction method using maximum entropy model. In contrast to previous methods, the proposed method has the ability to produce multiple best results for a given sentence, which is useful in text summarization applications. Experimental results show that the proposed method improves on earlier methods in both accuracy and computation time.