Disconnected Emerging Knowledge Graph Oriented Inductive Link Prediction

Yufeng Zhang, Weiqing Wang, Hongzhi Yin, Pengpeng Zhao, Wei Chen, Lei Zhao

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

11 Citations (Scopus)

Abstract

Inductive link prediction (ILP) is to predict links for unseen entities in emerging knowledge graphs (KGs), considering the evolving nature of KGs. A more challenging scenario is that emerging KGs consist of only unseen entities without any edge connected to original KGs, called as disconnected emerging KGs (DEKGs). Existing studies for DEKGs only focus on predicting enclosing links, i.e., predicting links inside the emerging KG. The bridging links, which carry the evolutionary information from the original KG to DEKG, have not been investigated by previous work so far. To fill in the gap, we propose a novel model entitled DEKG-ILP (Disconnected Emerging Knowledge Graph Oriented Inductive Link Prediction) that consists of the following two components. (1) The module CLRM (Contrastive Learning-based Relation-specific Feature Modeling) is developed to extract global relation-based semantic features that are shared between original KGs and DEKGs with a novel sampling strategy. (2) The module GSM (GNN-based Subgraph Modeling) is proposed to extract the local subgraph topological information around each link in KGs. The extensive experiments conducted on several benchmark datasets demonstrate that DEKG-ILP has obvious performance improvements compared with state-of-the-art methods for both enclosing and bridging link prediction.

Original languageEnglish
Title of host publicationProceedings - 2023 IEEE 39th International Conference on Data Engineering, ICDE 2023
EditorsIlaria Bartolini, Xiaochun Yang
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages381-393
Number of pages13
ISBN (Electronic)9798350322279
ISBN (Print)9798350322286
DOIs
Publication statusPublished - 2023
EventIEEE International Conference on Data Engineering 2023 - Anaheim, United States of America
Duration: 3 Apr 20237 Apr 2023
Conference number: 39th
https://ieeexplore.ieee.org/xpl/conhome/10184508/proceeding (Proceedings)

Conference

ConferenceIEEE International Conference on Data Engineering 2023
Abbreviated titleICDE 2023
Country/TerritoryUnited States of America
CityAnaheim
Period3/04/237/04/23
Internet address

Keywords

  • Inductive Link Prediction
  • Knowledge Graph
  • Knowledge Graph Embedding

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