Speeding up the Xbox recommender system using a euclidean transformation for inner-product spaces

RecSys, pp. 257-264, 2014.

Cited by: 89|Views22
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Abstract:

A prominent approach in collaborative filtering based recommender systems is using dimensionality reduction (matrix factorization) techniques to map users and items into low-dimensional vectors. In such systems, a higher inner product between a user vector and an item vector indicates that the item better suits the user's preference. Trad...More

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