Relation chaining in binary positive-only recommender systems

作者：

Highlights：

• Improved matrix completion on binary, positive-only data for recommender systems.

• Filtering for the number of intermediary objects improves data chaining.

• Evaluation on real and synthetic data with varying degree of transitivity.

• Faster computation time using chain matrix multiplication.

摘要

•Improved matrix completion on binary, positive-only data for recommender systems.•Filtering for the number of intermediary objects improves data chaining.•Evaluation on real and synthetic data with varying degree of transitivity.•Faster computation time using chain matrix multiplication.

论文关键词：Recommender systems,Data fusion,Matrix co-factorization,Relation chaining,Transitivity,Chain matrix multiplication

论文评审过程：Received 17 September 2019, Revised 3 February 2020, Accepted 5 February 2020, Available online 7 February 2020, Version of Record 25 February 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.113296