Item-based collaborative filtering recommendation algorithms

  title={Item-based collaborative filtering recommendation algorithms},
  author={Badrul Munir Sarwar and George Karypis and Joseph A. Konstan and John Riedl},
Recommender systems apply knowledge discovery techniques to the problem of making personalized recommendations for information, products or services during a l ive interaction. These systems, especially the k-nearest neighbor collaborative filtering based ones, are achieving widespread success on the Web. The tremendous growth in the amount of available information and the number of visito r Web sites in recent years poses some key challenges for recommender systems. These are: producing high… CONTINUE READING
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