@inproceedings{217b48782414416ba43f79fbb1ecd29f,
title = "Optimal recommender systems blending",
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.",
keywords = "collaborative filtering, optimization, recommender systems",
author = "Fabio Roda and Alberto Costa and Leo Liberti",
year = "2011",
month = jan,
day = "1",
doi = "10.1145/1988688.1988758",
language = "English",
isbn = "9781450301480",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
booktitle = "WIMS'11 - Proceedings of the International Conference on Web Intelligence, Mining and Semantics",
}