A cost-effective approach for mining near-optimal top-k patterns

作者：

Highlights：

• This study proposes a near-optimal top-k pattern mining approach.

• Computational cost is reduced through a newly early termination property.

• An optimal strategy is proposed to reduce the requirements of memory space.

• The algorithm is of great scalability as well as recall in real-life graphs.

摘要

•This study proposes a near-optimal top-k pattern mining approach.•Computational cost is reduced through a newly early termination property.•An optimal strategy is proposed to reduce the requirements of memory space.•The algorithm is of great scalability as well as recall in real-life graphs.

论文关键词：Frequent pattern mining,Graph mining,Social analysis

论文评审过程：Received 21 February 2022, Revised 10 April 2022, Accepted 13 April 2022, Available online 20 April 2022, Version of Record 30 April 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.117262