Electronic Science and Technology ›› 2022, Vol. 35 ›› Issue (12): 17-25.doi: 10.16180/j.cnki.issn1007-7820.2022.12.003

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Knowledge Graph Query Method Based on Geographic Location Information

LI Yipei,WANG Yuxiang   

  1. College of Computer Science and Technology,Hangzhou Dianzi University,Hangzhou 310018,China
  • Received:2021-05-06 Online:2022-12-15 Published:2022-12-13
  • Supported by:
    National Natural Science Foundation of China(62072149)

Abstract:

Existing knowledge graph query methods ignore the geographic location information of entities themselves, so they do not support geographic location related queries. In view of this problem, on the basis of the hybrid knowledge graph integrating geographic location information, this study proposes a knowledge graph query method based on geographic location information. By extracting the triples from the query problem, the corresponding query graph is constructed to understand the natural language query problem. The query problems based on geographic location information are divided into six categories, and combined with the existing semantic query methods for fact-based problems, the corresponding knowledge graph query methods are studied according to the query graph or K-nearest neighbor search idea. Experimental results show that the accuracy rate of the proposed method can reach more than 77%, which can provide effective support for query based on geographic location information.

Key words: knowledge graph, geographic location information, geographic entity, encyclopedic knowledge, graph query, semantic query, triple extraction, query graph

CLC Number: 

  • TP399