A Survey for Personalized Item based Recommendation System

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Provided by: International Journal of Emerging Trends & Technology in Computer Science (IJETTCS)
Topic: E-Commerce
Format: PDF
Recommendation techniques are very important in the fields of e-commerce and other Web-based services; one of the main difficulties is dynamically providing high-quality recommendation on sparse data. Here a novel personalized recommendation algorithm is proposed, in which information contained in both ratings and feedback of the user is considered, a set of dynamic features are designed to describe user preferences in multiple phases and finally a recommendation is made by adaptively weighting the features on the basis of result of rating and feedback by using the collaborative graph of both.
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