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A User Behavior-Based Agent for Improving Web Usage


Francesco Buccafurri, Gianluca Lax, Domenico Rosaci, and Domenico Ursino

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Abstract

Designing applications for supporting the user activity on accessing Web information sources is one of the most appealing challenges for researchers in the area of Artificial Intelligence. The agent paradigm represents a natural way of facing this problem, mainly because of the autonomy and reactivity properties which these applications should have. In this paper we design an agent capable of both creating and managing a personal ontology as well as of exploiting it for discovering navigation paths potentially interesting for the user. The agent, during the navigation of a site, provides the user with a set of recommendations and, at the same time, learns her/his preferences by updating the ontology. The power of the approach is based on the capability of the ontology model (called concept-graph) of representing user-behavior dependent relationships among concepts and, importantly, dealing with structural and semantic heterogeneity of Web sources.


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