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Inferring User Search using Feedback Session and Semantic Search

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Authors:
Deshmukh N. M., Patil B. M., Chandode V. M.
10.5120/ijca2017914921

Deshmukh N M., Patil B M. and Chandode V M.. Inferring User Search using Feedback Session and Semantic Search. International Journal of Computer Applications 170(7):31-35, July 2017. BibTeX

@article{10.5120/ijca2017914921,
	author = {Deshmukh N. M. and Patil B. M. and Chandode V. M.},
	title = {Inferring User Search using Feedback Session and Semantic Search},
	journal = {International Journal of Computer Applications},
	issue_date = {July 2017},
	volume = {170},
	number = {7},
	month = {Jul},
	year = {2017},
	issn = {0975-8887},
	pages = {31-35},
	numpages = {5},
	url = {http://www.ijcaonline.org/archives/volume170/number7/28086-2017914921},
	doi = {10.5120/ijca2017914921},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Different users may have diverse search goals for ambiguous queries when they put forward it to a search engine. Search engine relevance and user experience are enhanced by the analysis of user search goals. In this work, a novel approach has been proposed to infer user search goals for a query by clustering its feedback sessions represented by pseudo-documents. First, goals of particular queries by clustering feedback session are found which depends upon user click through logs. It can efficiently replicate goals of users. Secondly, to estimate query texts in user minds, clustered feedback session is mapped to pseudo documents. Then ‘CAP’ (Classified Average Precision) is used to appraise performance of user search goals. Finally, a new criterion is “Semantic code” is proposed in which one can find out a particular aim of user’s search.

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Keywords

User search goals, feedback sessions, semantic search and pseudo-documents.