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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 onlinedoi:10.1145/1242572.1242808 dblp:conf/www/IwataSY07 fatcat:imoarhuytbavlon6izehpdft5q