MMF predicts item ratings as weighted sums of attribute-level ratings, yielding better RMSE than MF, PMF, BPMF, LibFM, and DeepCrossing on MovieLens and Netflix subsets, while adding interpretability and cold-start ability.
A survey of recommendation system: Research challenges,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.IR 1years
2019 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
MMF: Attribute Interpretable Collaborative Filtering
MMF predicts item ratings as weighted sums of attribute-level ratings, yielding better RMSE than MF, PMF, BPMF, LibFM, and DeepCrossing on MovieLens and Netflix subsets, while adding interpretability and cold-start ability.