电子科技 ›› 2022, Vol. 35 ›› Issue (12): 17-25.doi: 10.16180/j.cnki.issn1007-7820.2022.12.003

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基于地理位置信息的知识图谱查询方法

李怡霈,王宇翔   

  1. 杭州电子科技大学 计算机学院,浙江 杭州 310018
  • 收稿日期:2021-05-06 出版日期:2022-12-15 发布日期:2022-12-13
  • 作者简介:李怡霈(1996-),女,硕士研究生。研究方向:知识图谱。|王宇翔(1986-),男,博士,讲师。研究方向:知识图谱、图查询、推荐系统等。
  • 基金资助:
    国家自然科学基金(62072149)

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)

摘要:

现有知识图谱查询方法忽略了实体本身的地理位置信息,故而不支持地理位置相关查询的问题。针对该问题,在融合地理位置信息的混合知识图谱的基础上,文中提出一种基于地理位置信息的知识图谱查询方法。通过抽取查询问题中的三元组,构建了相应的查询图以理解自然语言查询问题。将基于地理位置信息的查询问题分为6类,再结合已有事实类问题的语义查询方法,分别根据查询图或K近邻搜索思想研究相应的知识图谱查询方法。实验结果表明,文中所提方法的精确率可达77%以上,能够为基于地理位置信息的查询提供有效支持。

关键词: 知识图谱, 地理位置信息, 地理实体, 百科知识, 图查询, 语义查询, 三元组抽取, 查询图

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

中图分类号: 

  • TP399