document: Modeling user behavior in recommender systems based on maximum entropy 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 cartoon distribution service , and measure the recommendation effects for evaluating the recommender system .
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