Survey on Collaborative Filtering and Content-Based Recommending
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Abstract
Collaborative filtering (CF) is an important and popular technology for recommender systems. Recommender systems have been proven to be valuable means for web online users to cope with the information overload and have become one of the most powerful and popular tools in electronic commerce. Recommending and personalization are important approaches to combating information over-load.Machine Learning is an important part of systems for these tasks. Collaborative filtering has problems. Content-based methods address these problems (but have problems of their own).Integrating both is best.
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