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Collaborative filtering with maximum entropy

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4 Author(s)

As users navigate through online document collections on high-volume Web servers, they depend on good recommendations. We present a novel maximum-entropy algorithm for generating accurate recommendations and a data-clustering approach for speeding up model training. Recommender systems attempt to automate the process of "word of mouth" recommendations within a community. Typical application environments such as online shops and search engines have many dynamic aspects.

Published in:

IEEE Intelligent Systems  (Volume:19 ,  Issue: 6 )