Title :
Query-focused Summarization Based on Genetic Algorithm
Author :
Zhao, Xiaojuan ; Tang, Jun
Author_Institution :
Dept. of Inf. Eng., Hunan Urban Constr. Coll., Xiangtan, China
Abstract :
This paper proposed a new method of query-focused multi-documents summarization based on genetic algorithm, genetic algorithm is used to extract the sentences to form a summary, and it is based on a fitness function formed by three factors. Experimental result shows that the proposed summarization method can improve the performance of summary, genetic algorithm is efficient.
Keywords :
document handling; genetic algorithms; query formulation; fitness function; genetic algorithm; query-focused multidocuments summarization; Algorithm design and analysis; Ant colony optimization; Automation; Character generation; Clustering algorithms; Frequency; Genetic algorithms; Mechatronics; Proposals; Steady-state; genetic algorithm; sentence similarity; summarization;
Conference_Titel :
Measuring Technology and Mechatronics Automation (ICMTMA), 2010 International Conference on
Conference_Location :
Changsha City
Print_ISBN :
978-1-4244-5001-5
Electronic_ISBN :
978-1-4244-5739-7
DOI :
10.1109/ICMTMA.2010.429
