NDLI: Improving Information Retrieval Precision by Finding Related Queries with Similar Information Need Using Information Scent

Content Provider	IEEE Xplore Digital Library
Author	Chawla, S. Bedi, P.
Copyright Year	2008
Abstract	Web is a valuable source of information and it is expanding at an enormous speed. Search engines provide the interface to access to this vast pool of information. Users express their information need through the input query to retrieve the relevant information which does not prove to be effective as input query entered by the user is too short to get the information need of the user. To retrieve the information according to a particular information need from a big pool of information available on the web is a big challenge. This paper proposes a method to find the related queries which approximate the information need of the input query issued to the search engine. This is accomplished using Information scent and content of clicked pages in query sessions mining. Information scent is derived from the information foraging theory in which user behavior in the information environment is guided by information scent. Information need of the query sessions is modeled using information scent and content of clicked URLs and query sessions with similar information need are clustered. The clusters which closely approximate the information need of input query are used to suggest queries with similar information need for a given input query. The suggested queries are ranked in order of their degree of relevance with respect to information need of the input query. Retrieval precision of search engine is improved as suggested queries help to retrieve document relevant to the need of user efficiently and quickly. Experimental study has been conducted on the dataset collected from "Google" search engine Web history to confirm the improvement of precision of information retrieval.
Starting Page	486
Ending Page	491
File Size	268772
Page Count	6
File Format	PDF
ISBN	9780769532677
DOI	10.1109/ICETET.2008.23
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-07-16
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Clustering algorithms Games Search engine Information retrieval Motion pictures Information Scent Information Retrieval History Data mining Clustering Engines
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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