Improving Cross-domain Recommendation through Probabilistic Cluster-level Latent Factor Model-Extended Version

@inproceedings{Ren2015ImprovingCR,
  title={Improving Cross-domain Recommendation through Probabilistic Cluster-level Latent Factor Model-Extended Version},
  author={Siting Ren and Sheng Gao},
  booktitle={AAAI},
  year={2015}
}
Cross-domain recommendation has been proposed to transfer user behavior pattern by pooling together the rating data from multiple domains to alleviate the sparsity problem appearing in single rating domains. However, previous models only assume that multiple domains share a latent common rating pattern based on the user-item co-clustering. To capture diversities among different domains, we propose a novel Probabilistic Cluster-level Latent Factor (PCLF) model to improve the cross-domain… CONTINUE READING

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