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10

ESANN
2007

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Collaborative Filtering with interlaced Generalized Linear Models

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Collaborative Filtering with interlaced Generalized Linear Models

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Collaborative Filtering (CF) aims at ﬁnding patterns in a sparse matrix of contingency. It can be used for example to mine the ratings given by users on a set of items. In this paper, we introduce a new model for CF based on the Generalized Linear Models formalism. Interestingly, it shares speciﬁcities of the model-based and the factorization approaches. The model is simple, and yet it performs very well on the popular MovieLens and Jester datasets.

Nicolas Delannay, Michel Verleysen

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Collaborative Filtering | ESANN 2007 | Linear Models Formalism | Neural Networks | Sparse Matrix |

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Added	29 Oct 2010
Updated	29 Oct 2010
Type	Conference
Year	2007
Where	ESANN
Authors	Nicolas Delannay, Michel Verleysen

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