Heterogeneous Information Networks: the Past, the Present, and the Future

Yizhou Sun, Jiawei Han, Xifeng Yan, Philip S. Yu, Tianyi Wu

Research output: Contribution to journalConference articlepeer-review


In 2011, we proposed PathSim to systematically define and compute similarity between nodes in a heterogeneous information network (HIN), where nodes and links are from different types. In the PathSim paper, we for the first time introduced HIN with general network schema and proposed the concept of meta-paths to systematically define new relation types between nodes. In this paper, we summarize the impact of PathSim paper in both academia and industry. We start from the algorithms that are based on meta-path-based feature engineering, then move on to the recent development in heterogeneous network representation learning, including both shallow network embedding and heterogeneous graph neural networks. In the end, we make the connection between knowledge graphs and HINs and discuss the implication of meta-paths in the symbolic reasoning scenario. Finally, we point out several future directions.

Original languageEnglish (US)
Pages (from-to)3807-3811
Number of pages5
JournalProceedings of the VLDB Endowment
Issue number12
StatePublished - 2022
Event48th International Conference on Very Large Data Bases, VLDB 2022 - Sydney, Australia
Duration: Sep 5 2022Sep 9 2022

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • General Computer Science


Dive into the research topics of 'Heterogeneous Information Networks: the Past, the Present, and the Future'. Together they form a unique fingerprint.

Cite this