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User Profiling in an Application of Electronic Commerce

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AI*IA 2001: Advances in Artificial Intelligence (AI*IA 2001)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2175))

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Abstract

The COGITO 1 project aims at improving consumer-supplier relationships in future e-commerce interfaces featuring agents which can converse with users in written natural language (chatterbots) and extending their capabilities. In this paper we present the personalization component, developed in the COGITO system, that allows for the classification of users accessing an e-commerce web site through Machine Learning techniques. In the final implementation, the resulting user profiles will be further analyzed to automatically extract usage patterns from the data given about user communities. This helps content providers to tailor their offers to the customers. needs, and can be used to generate assumptions about new users, when they start to converse with the system.

COGITO is an EU-funded project in the 5th Framework Programme, (IST-1999-13347)

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References

  1. Pazzani, M., Billsus D., Learning and Revising User Profiles: The Identification of Interesting Web Sites, Machine Learning, Vol.27, 1997.

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  2. Frank E. and Witten I.H., Generating Accurate Rule Sets without Global Optimization, Proceedings of the International Conference on Machine Learning (ICML.98), 1998.

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  3. Witten, I.H., Frank, E., Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations. Morgan Kaufmann Publishers, CA. San Francisco, 1999.

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  4. Quinlan, J.R., C4.5: Programs for Machine Learning, 1993.

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  5. Orkin, M., Drogin, R., Vital Statistic. McGraw-Hill Book Company, 1993.

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© 2001 Springer-Verlag Berlin Heidelberg

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Abbattista, F., Fanizzi, N., Ferilli, S., Lops, P., Semeraro, G. (2001). User Profiling in an Application of Electronic Commerce. In: Esposito, F. (eds) AI*IA 2001: Advances in Artificial Intelligence. AI*IA 2001. Lecture Notes in Computer Science(), vol 2175. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45411-X_11

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  • DOI: https://doi.org/10.1007/3-540-45411-X_11

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42601-1

  • Online ISBN: 978-3-540-45411-3

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