CNAVER: A Content and Network-based Academic VEnue Recommender system

作者：

Highlights：

• We propose CNAVER: a scholarly venue recommendation system.

• Our work provides a fusion model of content-based features and network-based model.

• It addresses cold start issues and data sparsity, diversity and stability issues.

• Experiments on DBLP dataset shows that, CNAVER surpass state-of-the-art methods.

摘要

•We propose CNAVER: a scholarly venue recommendation system.•Our work provides a fusion model of content-based features and network-based model.•It addresses cold start issues and data sparsity, diversity and stability issues.•Experiments on DBLP dataset shows that, CNAVER surpass state-of-the-art methods.

论文关键词：Venue recommender system,Social network analysis,Meta-path analysis,Random walk with restart (RWR),Graph clustering,Rank-based fusion

论文评审过程：Received 24 April 2019, Revised 1 October 2019, Accepted 6 October 2019, Available online 17 October 2019, Version of Record 16 January 2020.

论文官网地址：https://doi.org/10.1016/j.knosys.2019.105092