Fusing frequent sub-sequences in the session-based recommender system

作者：

Highlights：

• Investigate the distribution of the frequent sub-sequences.

• Devise the FSM method to capture the importance of the frequent sub-sequences.

• Verify the FSM’s superiority in session-based RS by comparing it with baselines.

摘要

•Investigate the distribution of the frequent sub-sequences.•Devise the FSM method to capture the importance of the frequent sub-sequences.•Verify the FSM’s superiority in session-based RS by comparing it with baselines.

论文关键词：Graph neural network,Session-based recommender system,Frequent sub-sequences

论文评审过程：Received 7 November 2021, Revised 4 June 2022, Accepted 5 June 2022, Available online 13 June 2022, Version of Record 21 June 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.117789