基于GRUM与聚类的地理空间服务发现方法研究

Abstract

针对已有地理空间服务发现方法中语义信息处理手段不够有效，算法效率低等问题，提出了一种新的地理空间服务发现方法。首先采用了轻量级的地理资源统一模型GRUM来规范化服务数据，其次基于本体技术建立了服务的聚类关系，最后设计了相应的匹配策略和算法。实验结果表明，本文提出的方法能有效提高地理空间服务发现的性能，且较其它方法具有执行速度快和精度高的优点，是一种有效的地理空间服务发现解决方案。 To solve the problem of the lack of semantic information processing and the low efficiency, a new method of geospatial service discovery is presented in this paper. Firstly, the lightweight geographic resources unified model GRUM is adopted to standardize service data. Then, the clustering relations of geospatial services are established based on ontology technology. Finally, the corresponding matching strategy and algorithm are designed. Experimental results show that the proposed approach can effectively improve the performance of the geospatial service discovery and perform the advantages of high speed and precision compared with other methods. It is proved to be an effective solution for geospatial service discovery.