DocumentCode :
2558589
Title :
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
Link To Document :
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