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A Probabilistic Sentence Reduction Using Maximum Entropy Model
Minh LE NGUYEN Masaru FUKUSHI Susumu HORIGUCHI
IEICE TRANSACTIONS on Information and Systems
Publication Date: 2005/02/01
Print ISSN: 0916-8532
Type of Manuscript: PAPER
Category: Natural Language Processing
sentence reduction, text summarization, natural language processing, maximum entropy models,
Full Text: PDF(793.2KB)
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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.