SURVEY ON RECOMMENDER SYSTEMS FOR SOLVING COLD START PROBLEM
Publication Date : 28/03/2019
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Recommender system is an information filtering system which is used to extract the exact content from massive amount of data set based on user preference or behavior. It will become popular in various areas include news, research article, artificial intelligence, data mining, big data analytics, products, etc. The task of recommender system is to predict the user’s ratings for each item and ranking the items. In research area RS plays a major role. There are different approaches in recommender system such as time-aware, event-aware, content-aware and location-aware. This paper mainly focuses on the aspects of RS, issues and challenges of RS. It also includes the survey on cold start problem.
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