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
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;
Conference_Titel :
Natural Computation (ICNC), 2012 Eighth International Conference on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4577-2130-4
DOI :
10.1109/ICNC.2012.6234637