Recommender System for Animated Video
نویسنده
چکیده
Finding entertainment in the domain of animation is a challenging process that often forces many customers to ask others for assistance in forums or chat rooms. The manual process of recommending shows to one another based on often flimsy examples prevents many users from efficiently identifying media that suites their taste. Recommender systems, software tools and techniques for providing suggestions of items to a user [12] , present an exceptional use case for resolving this problem. In this paper we compare the various implementations and benefits of using the collaborative filtering (user based approach). Improving the identification of animation customers are interested in is a problem domain recommender systems are well suited for, benefiting both customers and vendors of such media. The aim of this study is to provide a proof of concept system capable of providing valuable recommendations based on show rankings.
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