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CPrefMiner: An Algorithm for Mining User Contextual Preferences Based on Bayesian Networks

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4 Author(s)
Sandra de Amo ; Sch. of Comput. Sci., Fed. Univ. of Uberlandia, Uberlandia, Brazil ; Marcos L. P. Bueno ; Guilherme Alves ; Nádia F. Silva

In this article we propose CPrefMiner, a mining technique for learning a Bayesian Preference Network (BPN) from a given sample of user choices. In our approach, user preferences are not static and may vary according to a multitude of user contexts. So, we name them Contextual Preferences. Contextual Preferences can be naturally expressed by a BPN. The method has been evaluated in a series of experiments executed on synthetic and real-world datasets and proved to be efficient to discover user contextual preferences.

Published in:

2012 IEEE 24th International Conference on Tools with Artificial Intelligence  (Volume:1 )

Date of Conference:

7-9 Nov. 2012