检索词优化与空间自适应的深网POI获取方法研究

Research on Deep Web POI acquisition based on retrieving word optimization and spatial adaptive

针对检索词库构建困难、数据请求量受限制等相关问题,该文提出一种基于独立覆盖率排序和空间自适应剖分的深网POI信息搜索方法,通过候选检索词初步构建、贪婪式探测搜索、检索词优化降维、空间自适应剖分爬行等主要流程,利用逐步逼近POI搜索的最大覆盖最优解,实现对深网POI信息的全量获取,大幅度提高深网POI数据的召回率与采集效率,该方法对于丰富地理信息资源、提升空间信息服务与内容管理能力具有重要意义。

In this paper,a deep-web POI information search method based on independent coverage ranking and spatial adaptive partition is proposed to solve the problems of difficult construction of retrieval word base and limited data request.By constructing candidate search terms,searching greedily,optimizing dimensionality reduction of search terms,and crawling spatially adaptive partitioning,the maximum coverage optimal solution of POI search is approached step by step,and the full POI information of deep web is obtained.It is of great significance to improve the recall rate and collection efficiency of POI data for enriching geographic information resources and improving the ability of spatial information service and content management.