Top-k Closest Pair Queries over Spatial Knowledge Graph

Fangwei Wu, Xike Xie, Jieming Shi

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)


Recently, RDF data has been enriched with spatial semantics enabling spatial keyword search. Research spatial keyword search over spatial RDF data focus on finding the spatial entities rooted at subtrees which cover given query keywords. In this work, we study how relevant spatial entity pairs can be efficiently retrieved, where the relevance is determined according to both spatial distances and textual similarities. The retrieved top-k closest pairs are ranked and then returned to users for the interests of business intelligence and recommendation. We propose a branch-and-bound framework associated with effective lower and upper bound pruning techniques and early stopping conditions for efficiently retrieving relevant top-k closet pairs. The results demonstrate the high efficiency of our proposal compared to baseline solutions.

Original languageEnglish
Title of host publicationDatabase Systems for Advanced Applications - 26th International Conference, DASFAA 2021, Proceedings
EditorsChristian S. Jensen, Ee-Peng Lim, De-Nian Yang, Wang-Chien Lee, Vincent S. Tseng, Vana Kalogeraki, Jen-Wei Huang, Chih-Ya Shen
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages16
ISBN (Print)9783030731939
Publication statusPublished - 2021
Event26th International Conference on Database Systems for Advanced Applications, DASFAA 2021 - Taipei, Taiwan
Duration: 11 Apr 202114 Apr 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12681 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference26th International Conference on Database Systems for Advanced Applications, DASFAA 2021


  • Closest pair query
  • Knowledge graph
  • Spatial keyword search

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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