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Issue title: Collective intelligent information and database systems
Guest editors: Ngoc-Thanh Nguyen, Manuel Núñez and Bogdan Trawiński
Article type: Research Article
Authors: Maleszka, Bernadetta*
Affiliations: Faculty of Computer Science and Management, Wroclaw University of Science and Technology, Wroclaw, Poland
Correspondence: [*] Corresponding author. Bernadetta Maleszka, Faculty of Computer Science and Management, Wroclaw University of Science and Technology, Wroclaw, Poland. Tel.: +48 71 320 29 38; Fax: +48 71 320 42 95; E-mail: Bernadetta.Maleszka@pwr.edu.pl.
Abstract: Information overload has become a very important aspect of information retrieval domain. Even if a user knows where to look for interesting information, he can have a problem with precisely formulating his information needs. A solution of the problem is personalization and recommendation system – they observe user activities, analyze them to discover important preferences. Based on these information the system can improve the effectiveness of the results. In this paper we present a method for determining user profile in a document retrieval system. We propose ontology-based profile. Such a structure allows to process semantic relations between users’ queries. We focus on methods for adapting profile because only up-to-date profile can help the user to obtained results that correspond with his information needs. We present a set of postulates for adaptation methods. Performed experimental evaluations of developed methods are promising.
Keywords: Document retrieval, knowledge integration, user profile adaptation, ontology-based user profile
DOI: 10.3233/JIFS-169124
Journal: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 2, pp. 1253-1263, 2017
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