Large-scale spectral clustering based on pairwise constraints

作者：

Highlights：

• We face the real-world problem of having a limited set of pairwise constraints.

• Using pairwise constraints connected components (CC) are generated.

• The points’ local neighborhoods of the same CC are dynamically adapted.

• Constraints propagation to CC neighborhoods to increase the clustering accuracy.

• Scalability is ensured by following a landmark strategy.

摘要

•We face the real-world problem of having a limited set of pairwise constraints.•Using pairwise constraints connected components (CC) are generated.•The points’ local neighborhoods of the same CC are dynamically adapted.•Constraints propagation to CC neighborhoods to increase the clustering accuracy.•Scalability is ensured by following a landmark strategy.

论文关键词：Spectral clustering,Semi-supervised,Sparse coding

论文评审过程：Received 26 August 2014, Revised 24 January 2015, Accepted 20 May 2015, Available online 12 June 2015, Version of Record 12 June 2015.

论文官网地址：https://doi.org/10.1016/j.ipm.2015.05.007