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The recommender system is widely used in many areas in the age of information overload. Collaborative filtering (CF), as one of the most successful methods used for recommendation, recommends items based on the nearest neighbors of the target user. Thus, the performance of the recommender system depends largely on the similarity measure used for selecting neighbors. Most of the traditional similarity...
In this paper we examine an advanced collaborative filtering method that uses similarity transitivity concepts. By propagating "similarity" between users, in a similar way as with "trust", we can significantly expand the space of potential recommenders and system's coverage, improving also the recommendations' accuracy. While "trust" information might be missing or be...
Trust -- aware recommender systems are intelligent technology applications that make use of trust information and user personal data in social networks to provide personalized recommendations. Recent research on recommender systems shows that these recommender systems are more robust against shilling attacks and can better be used for generating recommendations for new users. In this paper we proposed...
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