Large-scale recommender system with compact latent factor model

作者：

Highlights：

• A compact latent factor model for query-based recommendation is proposed.

• The proposed model can process data incrementally.

• The proposed model can deal with cold-start problems.

• The proposed model can extend to context-aware recommendation algorithm.

• The proposed algorithm outperforms other alternatives on three datasets.

摘要

•A compact latent factor model for query-based recommendation is proposed.•The proposed model can process data incrementally.•The proposed model can deal with cold-start problems.•The proposed model can extend to context-aware recommendation algorithm.•The proposed algorithm outperforms other alternatives on three datasets.

论文关键词：Recommender system,Latent factor model,Collaborative filtering,Content-based

论文评审过程：Received 6 March 2016, Revised 20 July 2016, Accepted 2 August 2016, Available online 3 August 2016, Version of Record 10 August 2016.

论文官网地址：https://doi.org/10.1016/j.eswa.2016.08.009