Abstract
This paper presents a Multi-Agent based web content categorization system. The system was prototyped using an Agents’ Framework for Internet data collection. The agents employ supervised learning techniques, specifically text learning to capture users preferences. The Framework and its application to E-commerce are described and the results achieve during the IST DEEPSIA project are shown. A detailed description of the most relevant system agents as well as their information flow is presented. The advantages derived from agent’s technology application are conferred.
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Sousa, P.A.C., Pimentão, J.P., Santos, B.R.D., Steiger Garção, A. (2004). Analysis of a Web Content Categorization System Based on Multi-agents. In: Favela, J., Menasalvas, E., Chávez, E. (eds) Advances in Web Intelligence. AWIC 2004. Lecture Notes in Computer Science(), vol 3034. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24681-7_21
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DOI: https://doi.org/10.1007/978-3-540-24681-7_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22009-1
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