Recommendations under sparsity

Recommendations under sparsity

In this talk, I look at the advantages and disadvantages of collaborative filtering and content-based recommenders when interaction data is sparse, and describe a hybrid approach implemented in the LightFM package.

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Maciej Kula

October 06, 2015
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