地球信息科学学报 ›› 2014, Vol. 16 ›› Issue (1): 39-44.doi: 10.3724/SP.J.1047.2014.00039

• 地球信息科学理论与方法 • 上一篇    下一篇

基于语义的GP服务多层次发现算法

魏海涛1,2, 杜云艳2, 何亚文3, 周成虎2, 张镭4   

  1. 1. 山东科技大学测绘科学与工程学院, 青岛 266510;
    2. 中国科学院地理科学与资源研究所 资源与环境信息系统国家重点实验室, 北京 100101;
    3. 中国石油大学地球科学与技术学院, 青岛 266580;
    4. 国家海洋信息中心网络与系统开发部, 天津 300171
  • 收稿日期:2013-05-15 修回日期:2013-07-04 出版日期:2014-01-05 发布日期:2014-01-05
  • 通讯作者: 杜云艳(1973-),女,副研究员,研究方向为海洋信息技术及应用。E-mail:duyy@lreis.ac.cn E-mail:duyy@lreis.ac.cn
  • 作者简介:魏海涛(1979-),女,博士生,研究方向为海洋服务集成算法。E-mail:Weiht@lreis.ac.cn
  • 基金资助:

    海洋公益性专项“海洋环境信息云计算与云服务体系框架应用研究”(201105033);海洋预报综合信息系统(MiFSIS)研究应用(201105017);中央高校基本科研业务费专项资金资助(14CX02033A)。

The Multi-level Discovery Algorithm of GP Service Based on Semantic Description

WEI Haitao1,2, DU Yunyan2, HE Yawen3, ZHOU Chenghu2, ZHANG Lei4   

  1. 1. Shandong University of Science and Technology, Qingdao 266510 China;
    2. LREIS, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
    3. China University of Petroleum, Qingdao 266580, China;
    4. National Marine Data and Information Service Department of Network Design & Development Tianjin 300171, China
  • Received:2013-05-15 Revised:2013-07-04 Online:2014-01-05 Published:2014-01-05

摘要:

随着云技术的飞速发展,“一切资源皆服务”成为可能,“数字地球”的实现也不例外。观测技术的快速发展使数据资源变得很丰富,但数据利用率低是普遍存在的现象,如何完成空间数据信息的再加工是亟待解决的问题,在云时代,具有数据处理功能的服务是解决此问题的方法之一,如何描述、发现和集成数据处理服务,从云端服务池中发现最优的服务是其关键所在。为了提高服务的查全率和查准率,引入了本体的概念,服务的语义描述很大程度上提高了空间数据处理服务的应用范围,缓解了非专业用户和专业人员之间的沟通障碍。本文分析了相关领域服务匹配算法的优缺点,结合GP服务自身的特点,提出了本体的GP服务的多层次发现算法:通过包含关系和线索关系完成服务间隐含关系的挖掘,主要是父子关系和前驱后继关系的表述;扩展传统本体表达模型,增加包含和线索关系,为服务的查找做准备;服务的多层次查找,第一次筛选主要针对服务预处理中包含和线索关系的表达查找,第二次筛选利用神经网络的突触原理,结合传统的服务匹配算法,完成服务的准确查找。经试验证明,此方法大大地提高了服务的查准率和查全率,具有重要的实践意义。

关键词: 云技术, 本体, 多层次, GP, 隐含关系, 数据处理服务, 语义

Abstract:

With the rapid development of cloud technology, "all resources are becoming services" and the "digital earth" is becoming realizable. Although the great progress of observational technology considerably enriched the available data resources, it raised quite a challenge of processing and reprocessing the spatial data of which the utilization ratio was generally low to date. The data processing service in today's cloud technology is an effective strategy for addressing this challenge, but the key solutions lie in how to describe, search and integrate the data processing services and how to find the optimal service in the cloud service pool. The service semantics based on the ontology theory are useful for bridging the knowledge gap between non-professional and professional clients and can help expand the application domains of spatial data processing services. So, this study, by comparing several service matching algorithms in related researches, presents a multi-level algorithm combining the ontology technique for searching the optimal Geoprocess (GP) service. The algorithm introduces the part-of and the sequential relation semantics to describe the parent-child relationships and the predecessor-successor relationships between different services. The multi-level searches are performed by first matching such relational semantics of the services and then executing a conventional service matching algorithm based on the synaptic theory in neural network. Finally, the experiment in this study confirmed the improvement of the algorithm upon the recall and precision ratio.

Key words: data processing services, ontology, semantic description, cloud technology, multi-level, implicit relationships, GP