Text Summarization Using Hybrid Parallel Genetic Algorithm

被引：0

作者：

Tang, Xinlai ^{[1
]}

Wang, XiaoRong ^{[2
]}

机构：

[1] GuangXi Univ Technol, Iushan Coll, Lizhou 545006, Peoples R China

[2] GuangXi Univ Technol, Dept Comp Engn, Lizhou 545006, Peoples R China

来源：

ADVANCED MATERIALS AND INFORMATION TECHNOLOGY PROCESSING, PTS 1-3 | 2011年 / 271-273卷

关键词：

Improved K-means Algorithm; Concept-Obtained; Summarization;

D O I：

10.4028/www.scientific.net/AMR.271-273.154

中图分类号：

G40 [教育学];

学科分类号：

040101 ; 120403 ;

摘要：

This paper proposes a special Chinese automatic summarization method based on Concept-Obtained and Improved K-means Algorithm. The idea of our approach is to obtain concepts of words based on HowNet, and use concept as feature, instead of word. We use conceptual vector space model and Improved K-means Algorithm to form a summarization. Experimental results indicate a clear superiority of the proposed method over the traditional method under the proposed evaluation scheme.

引用

页码：154 / +

页数：2

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