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Employing User Attribute and Item Attribute to Enhance the Collaborative Filtering Recommendation
2009
Journal of Software
Recommender systems are web based systems that aim at predicting a customer's interest on available products and services by relying on previously rated products and dealing with the problem of information and product overload. Collaborative filtering is the most popular recommendation technique nowadays and it mainly employs the user item rating data set. Traditional collaborative filtering approaches compute a similarity value between the target user and each other user by computing the
doi:10.4304/jsw.4.8.883-890
fatcat:6oubvn3k7bg3vegetnyjnlbexy