Local homogeneous consistent safe semi-supervised clustering
作者：
Highlights：
• We develop safe semi-supervised clustering which outperforms semi-supervised clustering.
• We construct a local homogeneous graph to safely exploit the risk prior knowledge.
• We can achieve the closed-form solution and obtain the promising results.
摘要
•We develop safe semi-supervised clustering which outperforms semi-supervised clustering.•We construct a local homogeneous graph to safely exploit the risk prior knowledge.•We can achieve the closed-form solution and obtain the promising results.
论文关键词：Semi-supervised clustering,Fuzzy c-means,Safe mechanism,Local homogeneous consistency
论文评审过程：Received 9 April 2017, Revised 27 November 2017, Accepted 28 December 2017, Available online 28 December 2017, Version of Record 8 January 2018.
论文官网地址：https://doi.org/10.1016/j.eswa.2017.12.046
