Detecting outlier pairs in complex network based on link structure and semantic relationship

作者：

Highlights：

• The differences between link and semantics are utilized to detect outlier pairs.

• A k-step index algorithm is proposed to calculate the term weighting.

• Frobenius norm and linear transformation are combined to rank the top-K differences.

• Direct and indirect link relations are both considered in link structure model.

摘要

•The differences between link and semantics are utilized to detect outlier pairs.•A k-step index algorithm is proposed to calculate the term weighting.•Frobenius norm and linear transformation are combined to rank the top-K differences.•Direct and indirect link relations are both considered in link structure model.

论文关键词：Outlier pair detection,Complex network,Link structure,Semantic relationship,K-step index

论文评审过程：Received 23 April 2016, Revised 10 October 2016, Accepted 12 October 2016, Available online 15 October 2016, Version of Record 24 October 2016.

论文官网地址：https://doi.org/10.1016/j.eswa.2016.10.026