Modeling user behavior in recommender systems based on maximum entropy

Tomoharu Iwata, Kazumi Saito, Takeshi Yamada
2007 Proceedings of the 16th international conference on World Wide Web - WWW '07  
We propose a model for user purchase behavior in online stores that provide recommendation services. We model the purchase probability given recommendations for each user based on the maximum entropy principle using features that deal with recommendations and user interests. The proposed model enable us to measure the effect of recommendations on user purchase behavior, and the effect can be used to evaluate recommender systems. We show the validity of our model using the log data of an online
more » ... artoon distribution service, and measure the recommendation effects for evaluating the recommender system.
doi:10.1145/1242572.1242808 dblp:conf/www/IwataSY07 fatcat:imoarhuytbavlon6izehpdft5q