应用具体域描述逻辑解决语义Web服务发现与组合问题

O. Zakharova
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引用次数: 0

摘要

本研究是一个普遍的科学和应用问题的分支之一,即使用和开发具有描述逻辑(DL)设备的本体论方法来获得基于面向服务架构的复杂业务任务的有效自动化解决方案的问题。该方法的基本思想是最大本体论,即任务的所有方面都是通过DL本体论来确定的。提出的本体系统基于五种基本的本体类型,即:(1)一般实体本体,用于定义服务上下文的特征;(2)应用领域本体,用于形式化和统一web服务的语义描述;(3)web服务顶层本体,用于一般web服务定义的深度形式化;(4)web服务任务本体,提供web服务生命周期所有阶段的任务的形式化表示。(5)特定web服务的本体。所有列出的本体都是相关的。因此,最后一种类型的本体包括到上述所有其他本体的链接,并与它们一起提供统一的正式定义的语义资源,从而支持web服务任务的自动解决方案。本研究的重点是将具有具体领域的描述性逻辑应用于web服务发现和组合等基本语义web服务任务的形式化。在本文中,web服务任务的本体被定义为具有特殊复杂概念的通用顶级web服务本体的扩展。它们的元素是“web服务-目标(请求)”/“web服务-web服务”对,它们根据要解决的任务进行比较。此外,在它们的基础上,还确定了特殊的复杂概念,这些概念指定了现有服务与发现任务中的目标之间的一组发现的相似性,或web服务的“前身-追随者”类型职责,以构建组合服务。提出的TBox语句使用具有具体域 𝓒()的描述性逻辑构造。为此,一个具体的领域被定义为一对集合:(1)参数概念的个体集合的可能子集的集合和上下文概念的个体集合的可能子集的集合的并集,以及(2)在其上定义的谓词集。具体领域的这种定义提供了仅使用功能角色来构造复杂概念DiscoveryServices和CompositionObject的DL语句以确定相应的web服务任务的可能性。注意,已定义的任务和web服务本体仅涵盖web服务表示的简化模型,特别是由上下文描述扩展的功能输入/输出模型。它们通过扩展该模型并将表示的功能模型和过程模型的附加特征涉及到指定的任务本体,为进一步改进提供了基础。这当然会提高所得结果的准确性,但这是进一步研究的课题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Applying Description Logics with Concrete Domains to Solve the Problems of Semantic Web Services Discovery and Composition
This research is one of the branches of a general scientific and applied problem, namely, the problem of using and developing ontological approaches with descriptive logics (DL) apparatus to obtain the effective automated solution of complex business task based on service-oriented architecture. The base idea of the proposed method is the maximal ontologization, that is, all aspects of the task are determined by means of DL ontologies. The proposed ontology system is based on five basic types of ontologies, namely: (1) an ontology of general entities for defining the characteristics of the service’s context, (2) an ontology of the application domain to formalize and unify semantical descriptions of web services, (3) the top-level ontology of web services for the DL formalization of the definition of the web services in general, (4) the ontologies of the web services tasks, which provide a formal representation of the tasks on all stages of web services life cycle, and (5) the ontologies of specific web services. All listed ontologies are related. Such, ontologies of the last type include links to all other above-mentioned ontologies and, together with them, provide a unified formally defined semantic resource, which enables the automatic solution of web service tasks. The focus of this study is the applying descriptive logics with concrete domains to the formalization of such basic semantic web services tasks as the web services discovery and composition. In this article, the ontologies of the web services tasks are defined as an extension of the general top-level web service ontology with special complex concepts. Their elements are pairs of “web service-goal (request)”/”web service-web service”, which are compared according to the task being solved. Also, on their basis, special complex concepts are determined, which specify a set of found similarities between existing services and a goal in the discovery task, or «predecessor-follower» type responsibilities of web services to build a composite service. The proposed TBox statements are constructed using descriptive logic with concrete domains 𝓐𝓛𝓒(𝓓). For this purpose, a concrete domain is defined as a pair of sets: (1) the union of sets of possible subsets of the set of individuals of the Parameter concept and possible subsets of the set of individuals of the Context concept, and (2) a set of predicates defined on it. Such definition of the concrete domain provides possibility of using only functional roles to construct the DL statements of complex concepts DiscoveryServices and CompositionObject for determining corresponding web services tasks. Note, the defined tasks and web services ontologies cover only simplified model of the representation of web services, in particular, functional Input/Output model extended by contexts descriptions. They provide the basis for further improvement by expanding this model and involving additional characteristics of both functional and process models of representation to the specified task ontologies. This will certainly increase the accuracy of the obtained result, but is the subject of further research.
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