DocumentCode :
2904771
Title :
Single document extractive text summarization using Genetic Algorithms
Author :
Chatterjee, Niladrish ; Mittal, Anish ; Goyal, Shri
Author_Institution :
Dept. of Math., Indian Inst. of Technol. Delhi, New Delhi, India
fYear :
2012
fDate :
Nov. 30 2012-Dec. 1 2012
Firstpage :
19
Lastpage :
23
Abstract :
This paper presents an extraction based single document text summarization technique using Genetic Algorithms. A given document is represented as a weighted Directed Acyclic Graph. A fitness function is defined to mathematically express the quality of a summary in terms of some desired properties of a summary, such as, topic relation, cohesion and readability. Genetic Algorithm is designed to maximize this fitness function, and get the corresponding summary by extracting the most important sentences. Results are compared with a couple of other existing text summarization methods keeping the DUC2002 data as benchmark, and using the precision-recall evaluation technique. The initial results obtained seem promising and encouraging for future work in this area.
Keywords :
directed graphs; genetic algorithms; text analysis; DUC2002 data; extraction based single document text summarization technique; fitness function; genetic algorithms; precision-recall evaluation technique; text summarization methods; weighted directed acyclic graph; Biological cells; Data mining; Genetic algorithms; Indexes; Sociology; Statistics; Vectors; Genetic Algorithms; Sentence Extraction; Text Summarization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Emerging Applications of Information Technology (EAIT), 2012 Third International Conference on
Conference_Location :
Kolkata
Print_ISBN :
978-1-4673-1828-0
Type :
conf
DOI :
10.1109/EAIT.2012.6407852
Filename :
6407852
Link To Document :
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