顾及语义知识的地理空间数据快速检索

Rapid Retrieval of Geospatial Data Considering Semantic Knowledge

  • 摘要: 大数据时代地理空间资源不断增多,但现有通用知识库较少考虑地理空间数据蕴含的语义知识,难以实现数据的快速检索。因此亟需引入本体技术,以蕴含的语义知识为基础,提高地理空间数据访问速度,精确获取用户所需信息。以本体为基础,提出了顾及地理空间数据语义知识的快速检索方法。首先,基于通名编码规则、地理空间数据和开源百度百科数据构建语义知识库;然后,定义查询重写规则,设计语义知识和空间数据库映射方式,基于地名自动构建检索语句;最后,通过实例应用和效率、质量对比分析验证快速检索方法的可行性。该方法以地理空间数据的语义知识为基础,仅通过地理实体名称即可自动构建数据库检索语句,减少用户对数据存储方式和数据库语法规则的依赖,有效提高系统的检索效率和智能化程度。

     

    Abstract:
      Objectives  In the era of big data, geospatial information resources are constantly increasing. However, the current knowledge bases are difficult to take into account the semantic knowledge as well as to retrieve geospatial data quickly. Therefore, it is urgent to introduce ontology technology to improve the access speed of geospatial data on the basis of semantic knowledge so as to accurately obtain the information needed by users.
      Methods  We propose a fast retrieval method that takes into account the semantic knowledge of geospatial data based on ontology. Firstly, a semantic knowledge base is constructed through encoding rules of generic place name, geospatial data and Baidu encyclopedia open source data. Secondly, we design some query rewrite rules and mapping methods between semantic knowledge and spatial database. So that we can construct retrieval statements based on place names automatically.
      Results  The feasibility of the fast retrieval method is verified through the application of an example and the comparative analysis of efficiency and quality.
      Conclusions  Based on the semantic information of geospatial data, we can automatically construct the structured query language(SQL) retrieval statement only by geographical entity name, reduce the user's dependence on data storage method and SQL grammar rules, and effectively improve the retrieval efficiency and intelligence of the system.

     

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