Abstract
In this paper, we propose a framework named UMT (User-profile Modeling based on Transactional data) for modeling user group profiles based on the transactional data. UMT is a generic framework for application systems that keep the historical transactions of their users. In UMT, user group profiles consist of three types: basic information attributes, synthetic attributes and probability distribution attributes. User profiles are constructed by clustering user transaction data and integrating cluster attributes with domain information extracted from application systems and other external data sources. The characteristic of UMT makes it suitable for personalization of transaction-based commercial application systems. A case study is presented to illustrate how to use UMT to create a personalized tourism system capable of using domain information in intelligent ways and of reacting to external events.
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© 2005 Springer-Verlag Berlin Heidelberg
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Yang, Y., Marques, N.C. (2005). User Group Profile Modeling Based on User Transactional Data for Personalized Systems. In: Bento, C., Cardoso, A., Dias, G. (eds) Progress in Artificial Intelligence. EPIA 2005. Lecture Notes in Computer Science(), vol 3808. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11595014_34
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DOI: https://doi.org/10.1007/11595014_34
Publisher Name: Springer, Berlin, Heidelberg
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