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Optimal recommender systems blending

Published:25 May 2011Publication History

ABSTRACT

In the Recommender Systems field ensemble techniques gain growing interest. This approach is based on the idea of mixing many recommenders and to get an average prediction from all of them. Even if it is useful this process may be very expensive from a computational point of view. We propose the use of Operations Research techniques in order to optimize the balance of different predictors and to accelerate it. We show that this problem can be generalized, thus we provide a mathematical framework which helps to find further improvements.

References

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  1. Optimal recommender systems blending

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              cover image ACM Other conferences
              WIMS '11: Proceedings of the International Conference on Web Intelligence, Mining and Semantics
              May 2011
              563 pages
              ISBN:9781450301480
              DOI:10.1145/1988688

              Copyright © 2011 ACM

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              Association for Computing Machinery

              New York, NY, United States

              Publication History

              • Published: 25 May 2011

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