Unsupervised binary feature construction method for networked data
作者：
Highlights：
• A novel feature construction algorithm is proposed for networked data.
• Attributes are reconstructed by exploiting structural data of network objects.
• An iterative local attribute selection method is applied for each object.
• Our method simulates the attribute space of objects in the same group.
• Our method can be used as pre-processing step by other methods.
摘要
•A novel feature construction algorithm is proposed for networked data.•Attributes are reconstructed by exploiting structural data of network objects.•An iterative local attribute selection method is applied for each object.•Our method simulates the attribute space of objects in the same group.•Our method can be used as pre-processing step by other methods.
论文关键词：Feature construction,Feature extraction,Feature selection,Link reconstruction,Social media,Networked data
论文评审过程：Received 10 July 2018, Revised 17 December 2018, Accepted 18 December 2018, Available online 18 December 2018, Version of Record 21 December 2018.
论文官网地址：https://doi.org/10.1016/j.eswa.2018.12.030
