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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,
Full Text: PDF(792.6KB)
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.
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