Cluster query: a new query pattern on temporal knowledge graph

Jinjing Huang, Wei Chen, An Liu, Weiqing Wang, Hongzhi Yin, Lei Zhao

Research output: Contribution to journalArticleResearchpeer-review

Abstract

A temporal knowledge graph (TKG) is theoretically a temporal graph. Recently, systems have been developed to support snapshot queries over temporal graphs. However, snapshot queries can only give separate answers. To retrieve forward-backward correlation facts from temporal knowledge graph, cluster query is proposed in this paper. To deal with the query, the logical view and physical model are presented. Subsequently, five corresponding basic query patters of unit matching are studied, and then the complete matchings are also addressed. To improve the query performance, index-based methods and pruning strategies are adopted. Experiments are conducted to evaluate cluster queries on three real datasets. The experimental results show the effectiveness and efficiency of cluster queries on temporal knowledge graphs.

Original languageEnglish
Pages (from-to)755-779
Number of pages25
JournalWorld Wide Web
Volume23
Issue number2
DOIs
Publication statusPublished - 13 Feb 2020

Keywords

  • Cluster query
  • Graph pattern matching
  • Temporal knowledge graph

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