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Reseach Article

Concept based Web Information Retrieval

by Jyotsna Gharat, Jayant Gadge
International Journal of Applied Information Systems
Foundation of Computer Science (FCS), NY, USA
Volume 4 - Number 5
Year of Publication: 2012
Authors: Jyotsna Gharat, Jayant Gadge
10.5120/ijais12-450713

Jyotsna Gharat, Jayant Gadge . Concept based Web Information Retrieval. International Journal of Applied Information Systems. 4, 5 ( October 2012), 25-29. DOI=10.5120/ijais12-450713

@article{ 10.5120/ijais12-450713,
author = { Jyotsna Gharat, Jayant Gadge },
title = { Concept based Web Information Retrieval },
journal = { International Journal of Applied Information Systems },
issue_date = { October 2012 },
volume = { 4 },
number = { 5 },
month = { October },
year = { 2012 },
issn = { 2249-0868 },
pages = { 25-29 },
numpages = {9},
url = { https://www.ijais.org/archives/volume4/number5/299-0713/ },
doi = { 10.5120/ijais12-450713 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2023-07-05T10:47:25.286100+05:30
%A Jyotsna Gharat
%A Jayant Gadge
%T Concept based Web Information Retrieval
%J International Journal of Applied Information Systems
%@ 2249-0868
%V 4
%N 5
%P 25-29
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Information retrieval is concerned with documents relevant to a user's information needs from a collection of documents. The user describes information needs with a query which consists of a number of words. Finding weight of a query is important to determine importance of a query. Calculating term importance is fundamental aspect of most information retrieval approaches and it is commonly determined through Term Frequency- Inverse Document Frequency (TF-IDF). This paper proposed Concept-based Term Weighting (CBW) technique to determine the term importance by finding the weight of a query. WordNet ontology is used to find the conceptual information of each word in the query.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Information Retrieval (IR) Part of Speech (POS) WordNet Ontology Concept-Based Term Weighting (CBW)