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SEMAPLAN: Combining Planning with Semantic Matching to Achieve Web Service Composition

机译:SEMAPLAN:将计划与语义匹配相结合以实现Web服务组合

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摘要

Composing existing Web services to deliver new functionality is a difficult problem as it involves resolving semantic, syntactic and structural differences among the interfaces of a large number of services. Unlike most planning problems, it can not be assumed that Web services are described using terms from a single domain theory. While service descriptions may be controlled to some extent in restricted settings (e.g., intra-enterprise integration), in Web-scale open integration, lack of common, formalized service descriptions prevent the direct application of standard planning methods. In this paper, we present a novel algorithm to compose Web services in the presence of semantic ambiguity by combining semantic matching and AI planning algorithms. Specifically, we use cues from domain-independent and domain-specific ontologies to compute an overall semantic similarity score between ambiguous terms. This semantic similarity score is used by AI planning algorithms to guide the searching process when composing services. Experimental results indicate that planning with semantic matching produces better results than planning or semantic matching alone. The solution is suitable for semi-automated composition tools or directory browsers.
机译:组合现有的Web服务以交付新功能是一个难题,因为它涉及解决大量服务的接口之间的语义,句法和结构差异。与大多数计划问题不同,不能假定使用来自单个域理论的术语来描述Web服务。虽然可以在受限制的设置中(例如企业内部集成)在某种程度上控制服务描述,但是在Web规模的开放集成中,缺少通用的,形式化的服务描述会阻止直接应用标准计划方法。在本文中,我们提出了一种新的算法,该算法通过将语义匹配和AI规划算法相结合,在存在语义歧义的情况下构成Web服务。具体来说,我们使用来自领域无关本体和领域特定本体的线索来计算歧义词之间的整体语义相似性评分。 AI计划算法使用此语义相似性评分来指导服务组合时的搜索过程。实验结果表明,具有语义匹配的计划比仅具有计划或语义匹配的计划产生更好的结果。该解决方案适用于半自动组合工具或目录浏览器。

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