A Multi-view Kernel Clustering framework for Categorical sequences

作者：

Highlights：

• A multi-view kernel clustering framework for categorical sequences is proposed.

• This method constructs the kernel matrix directly from the sequence views.

• A cluster validity index is proposed for categorical sequences.

• Experimentation on synthetic and real-world data sets.

摘要

•A multi-view kernel clustering framework for categorical sequences is proposed.•This method constructs the kernel matrix directly from the sequence views.•A cluster validity index is proposed for categorical sequences.•Experimentation on synthetic and real-world data sets.

论文关键词：Multi-view clustering,Kernel,Categorical sequences,Sample weighting,Cluster validation

论文评审过程：Received 30 August 2021, Revised 9 January 2022, Accepted 3 February 2022, Available online 22 February 2022, Version of Record 8 March 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.116637