Personalized Web Search Based on Ontological User Profile in Transportation Domain

ElShaweesh, O; Hussain, FK; Lu, H; Al-Hassan, M; Kharazmi, S

Personalized Web Search Based on Ontological User Profile in Transportation Domain

ElShaweesh, O Hussain, FK

Lu, H

Al-Hassan, M Kharazmi, S

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Publication Type:: Conference Proceeding
Citation:: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2017, 10637 LNCS pp. 239 - 248
Issue Date:: 2017-01-01

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Field	Value	Language
dc.contributor.author	ElShaweesh, O	en_US
dc.contributor.author	Hussain, FK https://orcid.org/0000-0003-1513-8072	en_US
dc.contributor.author	Lu, H https://orcid.org/0000-0001-5655-0237	en_US
dc.contributor.author	Al-Hassan, M	en_US
dc.contributor.author	Kharazmi, S	en_US
dc.date.issued	2017-01-01	en_US
dc.identifier.citation	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2017, 10637 LNCS pp. 239 - 248	en_US
dc.identifier.isbn	9783319700922	en_US
dc.identifier.issn	0302-9743	en_US
dc.identifier.uri	http://hdl.handle.net/10453/127380
dc.description.abstract	© 2017, Springer International Publishing AG. Current conventional search engines deliver similar results to all users for the same query. Because of the variety of user interests and preferences, personalized search engines, based on semantics, hold the promise of providing more efficient information that better reflects users’ needs. The main feature of building a personalized web search is to represent user interests in terms of user profiles. This paper proposes a personalized search approach using an ontology-based user profile. The aim of this approach is to build user profiles based on user browsing behavior and semantic knowledge of specific domain ontology to enhance the quality of the search results. The proposed approach utilizes a re-ranked algorithm to sort the results returned by the search engine to provide a search result that best relates to the user query. This algorithm evaluates the similarity between a user query, the retrieved search results and the ontological concepts. This similarity is computed by taking into account a user’s explicit browsing behavior, semantic knowledge of concepts, and synonyms of term-based vectors extracted from the WordNet API. A set of experiments using a case study from a transport service domain validates the effectiveness of the proposed approach and demonstrates promising results.	en_US
dc.relation.ispartof	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en_US
dc.relation.isbasedon	10.1007/978-3-319-70093-9_25	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	Personalized Web Search Based on Ontological User Profile in Transportation Domain	en_US
dc.type	Conference Proceeding
utslib.citation.volume	10637 LNCS	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	10637 LNCS	en_US

Abstract:

© 2017, Springer International Publishing AG. Current conventional search engines deliver similar results to all users for the same query. Because of the variety of user interests and preferences, personalized search engines, based on semantics, hold the promise of providing more efficient information that better reflects users’ needs. The main feature of building a personalized web search is to represent user interests in terms of user profiles. This paper proposes a personalized search approach using an ontology-based user profile. The aim of this approach is to build user profiles based on user browsing behavior and semantic knowledge of specific domain ontology to enhance the quality of the search results. The proposed approach utilizes a re-ranked algorithm to sort the results returned by the search engine to provide a search result that best relates to the user query. This algorithm evaluates the similarity between a user query, the retrieved search results and the ontological concepts. This similarity is computed by taking into account a user’s explicit browsing behavior, semantic knowledge of concepts, and synonyms of term-based vectors extracted from the WordNet API. A set of experiments using a case study from a transport service domain validates the effectiveness of the proposed approach and demonstrates promising results.

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http://hdl.handle.net/10453/127380