W-MetaPath2Vec: The topic-driven meta-path-based model for large-scaled content-based heterogeneous information network representation learning

作者：

Highlights：

• The efficiency improvement in network representation learning.

• Combination of network structure and topic similarity evaluation.

• High performance in network random walk mechanism.

• Capabilities in large-scaled information network handling.

摘要

•The efficiency improvement in network representation learning.•Combination of network structure and topic similarity evaluation.•High performance in network random walk mechanism.•Capabilities in large-scaled information network handling.

论文关键词：Heterogeneous information network,Representation learning,Topic similarity,Large-scaled network,Apache Spark

论文评审过程：Received 15 May 2018, Revised 3 October 2018, Accepted 4 January 2019, Available online 15 January 2019, Version of Record 23 January 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.01.015