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A Statistical Approach of Keyword Extraction for Efficient Retrieval

by Shruti Luthra, Dinkar Arora, Kanika Mittal, Anusha Chhabra
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 168 - Number 7
Year of Publication: 2017
Authors: Shruti Luthra, Dinkar Arora, Kanika Mittal, Anusha Chhabra
10.5120/ijca2017914443

Shruti Luthra, Dinkar Arora, Kanika Mittal, Anusha Chhabra . A Statistical Approach of Keyword Extraction for Efficient Retrieval. International Journal of Computer Applications. 168, 7 ( Jun 2017), 31-36. DOI=10.5120/ijca2017914443

@article{ 10.5120/ijca2017914443,
author = { Shruti Luthra, Dinkar Arora, Kanika Mittal, Anusha Chhabra },
title = { A Statistical Approach of Keyword Extraction for Efficient Retrieval },
journal = { International Journal of Computer Applications },
issue_date = { Jun 2017 },
volume = { 168 },
number = { 7 },
month = { Jun },
year = { 2017 },
issn = { 0975-8887 },
pages = { 31-36 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume168/number7/27889-2017914443/ },
doi = { 10.5120/ijca2017914443 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:16:06.747430+05:30
%A Shruti Luthra
%A Dinkar Arora
%A Kanika Mittal
%A Anusha Chhabra
%T A Statistical Approach of Keyword Extraction for Efficient Retrieval
%J International Journal of Computer Applications
%@ 0975-8887
%V 168
%N 7
%P 31-36
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Large number of techniques for keyword extraction have been proposed for better matching of documents with the user’s query but most of them deal with tf-idf to find the weight age of query terms in the entire document but this can result in improper result as if a term has a low term frequency in overall document but high frequency in a certain part of the document then that term can be ignored by traditional tf-idf method. Through this paper, the keyword extraction is improved using a hybrid technique in which the entire document is split into multiple domains using a master keyword and the frequency of all unique words is found in every domain . The words having high frequency are selected as candidate keywords and the final selection is made on the basis of a graph which is constructed between the keywords using Word Net. The experiments, conducted on various documents show that proposed approach outperforms other keyword extraction methodologies by enhancing document retrieval.

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Index Terms

Computer Science
Information Sciences

Keywords

Information Retrieval Domain Splitting Natural Language Processing Inverse Document Frequency Word Net

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