Meta-Circuit machine: Inferencing human collaborative relationships in heterogeneous information networks
作者：
Highlights：
• Human collaborative inference problems of two real-world networks are analysed.
• Meta-circuit random walks are proposed to extract training samples.
• Proportional controller is provided to improve imbalanced data problem.
• Meta-circuit recurrent neural network considering node and meta-path features is proposed.
• The effective reference for meta-circuit selection is provided.
摘要
•Human collaborative inference problems of two real-world networks are analysed.•Meta-circuit random walks are proposed to extract training samples.•Proportional controller is provided to improve imbalanced data problem.•Meta-circuit recurrent neural network considering node and meta-path features is proposed.•The effective reference for meta-circuit selection is provided.
论文关键词：Heterogeneous networks,Collaborative relationship,Meta-circuit,Random walk,00-01,99-00
论文评审过程：Received 23 June 2018, Revised 9 November 2018, Accepted 6 January 2019, Available online 8 February 2019, Version of Record 8 February 2019.
论文官网地址：https://doi.org/10.1016/j.ipm.2019.01.002
