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Reseach Article

Conceptual Weighing Query Expansion based on User Profiles

Published on November 2012 by Amita Jain, Kanika Mittal, Smita Sabharwal
National Conference on Communication Technologies & its impact on Next Generation Computing 2012
Foundation of Computer Science USA
CTNGC - Number 1
November 2012
Authors: Amita Jain, Kanika Mittal, Smita Sabharwal
6ce326f8-b080-4f5e-b03c-c9f57a2e7a0c

Amita Jain, Kanika Mittal, Smita Sabharwal . Conceptual Weighing Query Expansion based on User Profiles. National Conference on Communication Technologies & its impact on Next Generation Computing 2012. CTNGC, 1 (November 2012), 11-15.

@article{
author = { Amita Jain, Kanika Mittal, Smita Sabharwal },
title = { Conceptual Weighing Query Expansion based on User Profiles },
journal = { National Conference on Communication Technologies & its impact on Next Generation Computing 2012 },
issue_date = { November 2012 },
volume = { CTNGC },
number = { 1 },
month = { November },
year = { 2012 },
issn = 0975-8887,
pages = { 11-15 },
numpages = 5,
url = { /proceedings/ctngc/number1/9047-1003/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Communication Technologies & its impact on Next Generation Computing 2012
%A Amita Jain
%A Kanika Mittal
%A Smita Sabharwal
%T Conceptual Weighing Query Expansion based on User Profiles
%J National Conference on Communication Technologies & its impact on Next Generation Computing 2012
%@ 0975-8887
%V CTNGC
%N 1
%P 11-15
%D 2012
%I International Journal of Computer Applications
Abstract

Proper query terms significantly affect the performance of information retrieval systems. In this paper, a conceptual weighting method for query expansion is proposed with the help of user profile. Here, the users' initial queries and the retrieved documents based on the user's query (top n relevant documents) are analyzed and then the relevant terms from the documents retrieved are weighted. The terms having higher weight and the terms from the previous searches with a greater threshold weight will be selected and are used to derive the concepts in the concept network which are then connected to the phrases. Based on the matching of those phrases with that of the query phrases, additional query terms are selected and based on those additional query terms, the user's original query is expanded and the search is enhanced.

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Index Terms

Computer Science
Information Sciences

Keywords

Natural Language Processing Query Expansion Term-weighting Concept Networks User Profiles Information Retrieval