Computer Science ›› 2019, Vol. 46 ›› Issue (2): 171-177.doi: 10.11896/j.issn.1002-137X.2019.02.027

Special Issue: Database Technology

• Software & Database Technology • Previous Articles     Next Articles

Geo-semantic Data Storage and Retrieval Mechanism Based on CAN

LU Hai-chuan, FU Hai-dong, LIU Yu   

  1. College of Computer Science and Technology,Wuhan University of Science and Technology,Wuhan 430065,China
    Hubei Province Key Laboratory of Intelligent Information Processing and Real Time Industrial System,Wuhan 430065,China
  • Received:2018-08-16 Online:2019-02-25 Published:2019-02-25

Abstract: Semantic technology can search information more intelligently and accurately,and assist researchers to make scientific decisions.Therefore,this technology has been introduced into geographic information processing and formed a geo-query language GeoSPARQL based on RDF (Resource Description Framework).However,the existing application platforms based on geographic semantic information processing adopt centralized storage and retrieval services,which will cause the disadvantages of single node failure and poor scalability.Although researchers have proposed a variety of methods to use peer-to-peer network to improve the reliability and scalability of application systems,these methods do not consider the characteristics of geographic semantic data.In view of the above problems,this paper considered the feature of geographical semantic data and optimized the storage of semantic data on the peer-to-peer network.This paper proposed a storage and retrieval scheme based on content addressed network,and also improved the retrieval efficiency of semantic data by mapping the triple to the network according to its position.The experimental results show that the proposed scheme has good expansibility,and the query efficiency of topology relation is superior to the existing schemes.

Key words: Content addressable network, Geo-semantic information, GeoSPARQL, RDF storage and query

CLC Number: 

  • TP311
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