MEMORY: A Matrix-Based Efficient Semantic Web Service Discovery System

Zhuo Zhao, Dian-fu Ma, Jing Li, X. Qu
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引用次数: 3

Abstract

With the advance of Semantic Web, the adoption of Semantic Web has been regarded as the most promising way to improve the recall rate and precision rate of service discovery. However, Semantic Web Service discovery (SWS) is essentially not used on a large scale in real business world due to its time consuming performance and weak support for the QoS-based discovery. In order to solve these problems, this paper presents a matrix-based efficient SWS discovery system, namely MEMORY. MEMORY does ontological pre-reasoning and holds the reasoning results in matrix forms in service publishing phase, so that it can transfer the load of semantic reasoning from service query to service publication and perform fast matching during service discovery. The experiments in the end are conducted to further demonstrate the feasibility of our proposed matching approach and its high efficiency.
内存:一个基于矩阵的高效语义Web服务发现系统
随着语义网的发展,采用语义网被认为是提高服务发现的查全率和查准率最有希望的方法。然而,语义Web服务发现(SWS)由于其耗时的性能和对基于qos的发现的弱支持,在实际业务世界中基本上没有大规模使用。为了解决这些问题,本文提出了一种基于矩阵的高效SWS发现系统,即MEMORY。MEMORY在服务发布阶段进行本体预推理,将推理结果以矩阵形式保存,从而将语义推理的负荷从服务查询转移到服务发布,并在服务发现阶段进行快速匹配。最后通过实验进一步验证了本文提出的匹配方法的可行性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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