IJERT-EMS
IJERT-EMS

Context Based Indexing in Text Summarization Using Lexical Association


Context Based Indexing in Text Summarization Using Lexical Association
Authors : Dipti D. Pawar, Prof. M. S. Bewoor, Dr. S. H. Patil
Publication Date: 02-12-2013

Authors

Author(s):  Dipti D. Pawar, Prof. M. S. Bewoor, Dr. S. H. Patil

Published in:   International Journal of Engineering Research & Technology

License:  This work is licensed under a Creative Commons Attribution 4.0 International License.

Website: www.ijert.org

Volume/Issue:   Vol.2 - Issue 12 (December - 2013)

e-ISSN:   2278-0181

Abstract

World Wide Web today is a largest source of online- information. Great amount of information is present on internet in the form of web pages. There has been a huge amount of work on query specific summarization of documents using similarity measure. Indexing weights of the document terms are utilized to compute the sentence similarity value which remains independent on context. Very little work has been done for the problem of context independent document indexing for the text summarization task. The main contribution of this research work is to combine both approaches of Lexical association and context sensitive indexing. While doing so we have also used novel concept of Lexical association between terms to measure the similarity between sentences using computed indexing Weights. The proposed concept of sentence similarity measure has been used with the graph-based ranking method to create document graph and obtain summary of document.

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