Joint multi-label learning and feature extraction for temporal link prediction

作者：

Highlights：

• We show multi-label learning can be applied to temporal link prediction.

• We propose a joint algorithm for temporal link prediction by fusing multilabel learning and feature extraction.

• The proposed algorithm outperforms the state-of-the-art approaches on various temporal networks without increasing time complexity.

摘要

•We show multi-label learning can be applied to temporal link prediction.•We propose a joint algorithm for temporal link prediction by fusing multilabel learning and feature extraction.•The proposed algorithm outperforms the state-of-the-art approaches on various temporal networks without increasing time complexity.

论文关键词：Temporal link prediction,Non-negative matrix factorization,Multi-label learning,Dynamic networks

论文评审过程：Received 3 December 2019, Revised 7 May 2021, Accepted 28 July 2021, Available online 6 August 2021, Version of Record 13 August 2021.

论文官网地址：https://doi.org/10.1016/j.patcog.2021.108216