基于CAN的地理语义数据存储与检索机制

doi:10.11896/j.issn.1002-137X.2019.02.027

摘要/Abstract

摘要： 语义技术能够更智能、更精确地检索信息,辅助工作人员进行科学决策,已被应用于地理信息处理,并形成了基于RDF(Resource Description Framework)数据的地理查询语言GeoSPARQL。然而,基于地理语义信息处理的应用平台多采用中心化的存储和检索服务,使得这些平台存在单节点失效、扩展性差等缺陷。尽管已有研究人员提出了多种方法,试图利用对等网络技术来解决语义数据的分布式处理,从而提升应用系统的可靠性和扩展性,但这些方法并没有考虑地理语义数据自身的特征。针对上述问题,文中利用地理语义数据的特征在对等网络上对其进行存储,提出基于CAN(Content Addressable Network)的地理语义存储和检索方案,根据位置信息将地理语义数据映射到对等网络中,从而提高了语义数据的检索效率。实验结果表明,所提方案不仅具有良好的扩展性,而且地理信息的拓扑关系查询效率优于现有方案。

关键词: GeoSPARQL, RDF存储查询, 地理语义信息, 内容寻址网络

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

中图分类号:

TP311

卢海川, 符海东, 刘宇. 基于CAN的地理语义数据存储与检索机制[J]. 计算机科学, 2019, 46(2): 171-177. https://doi.org/10.11896/j.issn.1002-137X.2019.02.027

LU Hai-chuan, FU Hai-dong, LIU Yu. Geo-semantic Data Storage and Retrieval Mechanism Based on CAN[J]. Computer Science, 2019, 46(2): 171-177. https://doi.org/10.11896/j.issn.1002-137X.2019.02.027

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