Extract summarization using Concept-Obtained and Hybrid Parallel Genetic Algorithm

Author

Wang Meng ; Tang Xinlai

Author_Institution

Dept. of Comput. Eng., GuangXi Univ. of Technol., LiuZhou, China

fYear

2012

fDate

29-31 May 2012

Firstpage

662

Lastpage

664

Abstract

This paper proposes a special Chinese automatic summarization method based on Concept-Obtained and Hybrid Parallel Genetic Algorithm. The idea of our approach is to obtain concepts of words using HowNet as tool, and use concepts as feature, not words. We construct conceptual vector space model and use Hybrid Parallel Genetic Algorithm to form summary of documents. The automatic evaluation of document´s summaries with n-gram score shows the system´s effectiveness and feasibility.

Keywords

Internet; genetic algorithms; information retrieval; natural languages; parallel algorithms; text analysis; Chinese automatic summarization method; HowNet; Internet; automatic document summary evaluation; concept-obtained genetic algorithm; conceptual vector space model; extract summarization; hybrid parallel genetic algorithm; n-gram score; text documents; Biological cells; Clustering algorithms; Educational institutions; Encoding; Genetic algorithms; Internet; Vectors; Concept-Obtained; Hybrid Parallel Genetic Algorithm; Summarization;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Computation (ICNC), 2012 Eighth International Conference on

Conference_Location

Chongqing

ISSN

2157-9555

Print_ISBN

978-1-4577-2130-4

Type

conf

DOI

10.1109/ICNC.2012.6234637

Filename

6234637