论文标题
自动语义网络服务中的参数描述的关系模型
Relational Model for Parameter Description in Automatic Semantic Web Service Composition
论文作者
论文摘要
自动服务组成是一个研究方向,旨在促进原子网络服务的使用。特别是,目标是建立解决特定查询的服务工作流,这些问题无法通过已知存储库中的任何单个服务来解决。这些服务中的每一个都由其提供者独立描述,这些提供商无法彼此相互作用,因此已经开发了一些共同的标准,例如WSDL,BPEL,OWL-S。我们的建议是将这些标准与JSON-LD一起使用,以建模下一个语义级别,主要基于服务参数之间的二进制关系。服务与公共本体论有关以描述其功能。可以在服务定义中的输入和/或输出参数之间指定二进制关系。本体论包括一些关系和推理规则,有助于推断服务参数之间的新关系。据我们所知,这是第一次将参数不仅基于其类型,而且在考虑到这种类型的关系的更有意义的语义上下文中匹配。这使人可以在手动构建作品时会做到的大部分理由的自动化。此外,提出的模型和组成算法可以与同一类型的多个对象一起使用,这是以前无法的基本特征。我们认为,较差的模型表现力是防止服务组成在实践中达到大规模应用的原因。
Automatic Service Composition is a research direction aimed at facilitating the usage of atomic web services. Particularly, the goal is to build workflows of services that solve specific queries, which cannot be resolved by any single service from a known repository. Each of these services is described independently by their providers that can have no interaction with each other, therefore some common standards have been developed, such as WSDL, BPEL, OWL-S. Our proposal is to use such standards together with JSON-LD to model a next level of semantics, mainly based on binary relations between parameters of services. Services relate to a public ontology to describe their functionality. Binary relations can be specified between input and/or output parameters in service definition. The ontology includes some relations and inference rules that help to deduce new relations between parameters of services. To our knowledge, it is for the first time that parameters are matched not only based on their type, but on a more meaningful semantic context considering such type of relations. This enables the automation of a large part of the reasoning that a human person would do when manually building a composition. Moreover, the proposed model and the composition algorithm can work with multiple objects of the same type, a fundamental feature that was not possible before. We believe that the poor model expressiveness is what is keeping service composition from reaching large-scale application in practice.