Computational Intelligence techniques for Web personalization

Article type: Research Article

Authors: Castellano, G. | Fanelli, A.M. | Torsello, M.A.

Affiliations: Computer Science Department, Via Orabona, 4 - 70126 Bari, Italy

Note: [] Corresponding author. E-mail: [email protected].

Abstract: Computational Intelligence (CI) paradigms reveal to be potential tools to face under the Web uncertainty. In particular, CI techniques may be properly exploited to handle Web usage data and develop Web-based applications tailored on users preferences. The main rationale behind this success is the synergy resulting from CI components, such as fuzzy logic, neural networks and genetic algorithms. In fact, rather than being competitive, each of these computing paradigms provides complementary reasoning and searching methods that allow the use of domain knowledge and empirical data to solve complex problems. This paper focuses on the major Computational Intelligent combinations applied in the context of Web personalization, by providing different examples of intelligent systems which have been designed to provide Web users with the information they search, without expecting them to ask for it explicitly. In particular, this paper emphasizes the suitability of hybrid schemes deriving from the profitable combination of different CI methodologies for the development of effective Web personalization systems.

Keywords: Computational Intelligence, neuro-fuzzy model, Web personalization, Web recommendation, Web usage mining

DOI: 10.3233/WIA-2008-0140

Journal: Web Intelligence and Agent Systems: An International Journal, vol. 6, no. 3, pp. 253-272, 2008