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Strategy for Hindi Text Summarization using Content Based Indexing Approach

S. Sargule1 , R.M. Kagalkar2

Section:Research Paper, Product Type: Journal Paper
Volume-4 , Issue-9 , Page no. 36-42, Sep-2016

Online published on Sep 30, 2016

Copyright © S. Sargule, R.M. Kagalkar . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: S. Sargule, R.M. Kagalkar, “Strategy for Hindi Text Summarization using Content Based Indexing Approach,” International Journal of Computer Sciences and Engineering, Vol.4, Issue.9, pp.36-42, 2016.

MLA Style Citation: S. Sargule, R.M. Kagalkar "Strategy for Hindi Text Summarization using Content Based Indexing Approach." International Journal of Computer Sciences and Engineering 4.9 (2016): 36-42.

APA Style Citation: S. Sargule, R.M. Kagalkar, (2016). Strategy for Hindi Text Summarization using Content Based Indexing Approach. International Journal of Computer Sciences and Engineering, 4(9), 36-42.

BibTex Style Citation:
@article{Sargule_2016,
author = {S. Sargule, R.M. Kagalkar},
title = {Strategy for Hindi Text Summarization using Content Based Indexing Approach},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {9 2016},
volume = {4},
Issue = {9},
month = {9},
year = {2016},
issn = {2347-2693},
pages = {36-42},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1052},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1052
TI - Strategy for Hindi Text Summarization using Content Based Indexing Approach
T2 - International Journal of Computer Sciences and Engineering
AU - S. Sargule, R.M. Kagalkar
PY - 2016
DA - 2016/09/30
PB - IJCSE, Indore, INDIA
SP - 36-42
IS - 9
VL - 4
SN - 2347-2693
ER -

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Abstract

The Document summarization provides summary of document in a very short time. Existing systems for document summarization have work carried on English text summarization. Such systems do not consider the context of the word to produce summary. Previously implemented document summarization models generally use the similarity among sentences in the original document to extract the most relevant sentences. The documents along with the sentences are generally indexed using standard term indexing computation methods, which do not take into account the context related to document. System takes Hindi document as input. That document undergoes through the algorithm and final output is produced as summary of input Hindi document by considering the context of the word. The Bernoulli Model of Randomness technique is used to check the probability of co-occurrences of two terms in large corpus. The methodology used contains lexical association, sentences indexing, word indexing.

Key-Words / Index Term

Document Summarization, Lexical Association, Context Indexing

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