A Novel clustering method based on hybrid K-nearest-neighbor graph

作者：

Highlights：

• A novel data model termed hybrid k-nearest-neighbor graph is proposed to represent the data sets.

• A clustering method is developed based on the hybrid k-nearest-neighbor graph.

• A novel internal validity index is proposed to evaluate the validity of nonlinear clustering results.

摘要

•A novel data model termed hybrid k-nearest-neighbor graph is proposed to represent the data sets.•A clustering method is developed based on the hybrid k-nearest-neighbor graph.•A novel internal validity index is proposed to evaluate the validity of nonlinear clustering results.

论文关键词：Graph clustering,Hybrid k-nearest-neighbor graph,Internal validity index,Nonlinear data set,Video clustering

论文评审过程：Received 24 November 2016, Revised 24 August 2017, Accepted 5 September 2017, Available online 6 September 2017, Version of Record 12 September 2017.

论文官网地址：https://doi.org/10.1016/j.patcog.2017.09.008