Class-aware tensor factorization for multi-relational classification
作者：
Highlights：
• Introduced a new semi-supervised tensor factorization approach.
• Presented a joint optimization method which combines tensor factorization and a classification error term.
• Demonstrated effective performance in multiple real-world datasets.
摘要
•Introduced a new semi-supervised tensor factorization approach.•Presented a joint optimization method which combines tensor factorization and a classification error term.•Demonstrated effective performance in multiple real-world datasets.
论文关键词：Semi-supervised tensor factorization,Multi-relational networks,Social network analysis
论文评审过程：Received 15 November 2018, Revised 21 June 2019, Accepted 21 June 2019, Available online 9 July 2019, Version of Record 13 January 2020.
论文官网地址：https://doi.org/10.1016/j.ipm.2019.102068
