结合Rete的RDF数据分布式并行推理算法*

现有的资源描述框架(RDF)数据分布式并行推理算法大多需要启动多个MapReduce任务,但有些算法对于含有实例三元组前件的RDFS/OWL规则的推理效率低下,整体推理效率不高。针对此问题,文中提出结合Rete的RDF数据分布式并行推理算法(DRRM)。首先结合RDF数据本体,构建模式三元组列表和规则标记模型。在RDFS/OWL推理阶段,结合MapReduce实现Rete算法中的alpha阶段和beta阶段。然后对推理结果进行去重处理,完成一次RDFS/OWL全部规则推理。实验表明,文中算法能高效正确地实现大规模数据的并行推理。     

基于RDFS的本体集成方法

现实中的数据源一般具有半结构化、异构性和分布性等特点,而许多应用需要对不同的相关数据源进行联合操作。本体集成是解决知识共享、异构数据源语义互操作的有力工具。首先分析了本体集成的原因,提出了本体集成时应遵循的4条基本原则;然后提出了一种基于RDFS图闭包的本体集成方法,该方法将RDFS本体抽象为图模型,根据RDFS推理规则和扩展规则生成RDFS本体的图闭包,在此基础上进行本体集成,同时提出了几种计算实体间相似度的方法。最后,将该方法与FCA-merge和COMA++进行实验对比。     

扩展AL-log挖掘日志本体的ILP方法

为发现Web使用记录中所蕴涵的用户访问模式,在深入分析日志本体中事件间的抽象关系后,提出适用于原子事件和复合事件间整分关系推理的ALC传播规则扩展已有的推理模式,并在此基础上提出一种挖掘日志本体的ILP方法.该方法结合描述逻辑和Horn规则在知识表示和推理过程中互补的特点,采用AL-log混合系统构建知识库,利用约束SLD-反驳消解和扩展ALC传播规则从日志本体中学习用户访问模式,达到站点商业智能和个性化的目的.最后给出验证该方法的实例,实验结果表明了该方法的可行性和有效性.     

基于OWL的规则推理研究及应用

文中通过对基于OWL的本体构造方法,Jena通用推理机及推理规则的研究,尝试一种新的本体构造方法,以及针对此类本体所适用的规则.期望可以不局限于推理本体间的关系,而是能够针对本体的活动进行推理.为了证明该方法的可行性,实现了一个推理系统,在本体的构造过程中,加入了时间轴,并对其进行了推理研究.通过该推理系统及特殊的推理规则,可以利用本体间的关系或是本体基于时间轴的活动,推理出目标本体的活动.因此证明了该方法可以基于时间轴,有效地推理本体的活动.     

RDB中基于RDFS的语义本体存储技术研究

资源描述框架(RDF)/资源描述框架模式(RDFS)是语义互联网架构中的技术。尽管XML/RDF数据库正迅速的发展,关系型数据库仍是目前企业级应用的首选。针对如何有效地把RDFS数据存储在关系数据库中,充分利用现有的数据库资源来管理RDFS数据,提出了一种RDB中基于RDFS的语义本体存储技术,实现了RDFS本体抽取,提出了RDFS本体的存储优化方案,提高了数据存储访问效率。     

扩展AL log挖掘日志本体的ILP方法*

为发现Web使用记录中所蕴涵的用户访问模式,在深入分析日志本体中事件间的抽象关系后,提出适用于原子事件和复合事件间整分关系推理的ALC传播规则扩展已有的推理模式,并在此基础上提出一种挖掘日志本体的ILP方法。该方法结合描述逻辑和Horn规则在知识表示和推理过程中互补的特点,采用ALlog混合系统构建知识库,利用约束SLD反驳消解和扩展ALC传播规则从日志本体中学习用户访问模式,达到站点商业智能和个性化的目的。最后给出验证该方法的实例,实验结果表明了该方法的可行性和有效性。     

基于OWL的规则推理研究及应用

文中通过对基于OWL的本体构造方法,Jena通用推理机及推理规则的研究,尝试一种新的本体构造方法,以及针对此类本体所适用的规则。期望可以不局限于推理本体间的关系,而是能够针对本体的活动进行推理。为了证明该方法的可行性,实现了一个推理系统,在本体的构造过程中,加入了时间轴,并对其进行了推理研究。通过该推理系统及特殊的推理规则,可以利用本体间的关系或是本体基于时间轴的活动,推理出目标本体的活动。因此证明了该方法可以基于时间轴,有效地推理本体的活动。     

使用本体和SWRL验证作战计划的方法

计划验证是计划编制过程的重要环节。从知识管理的角度,在已有计划表示和计划推理相关研究的基础上,提出了一种基于本体和规则的计划验证方法框架,通过对计划知识进行基于本体的表示、基于描述逻辑、一阶谓词逻辑的规则知识抽取和计划推理,以实现对计划的验证。并以某排雷作战计划的验证为例进行了实验。实验表明,该方法实现了对专家知识的扩展,提高了作战计划正确性检验的效率。     

基于领域本体的语义合成研究

为了在检索过程中全面挖掘用户查询信息,文中提出了一种基于领域本体的语义合成技术,该方法以文本为数据源,引用数据源和领域本体之间的映射关系来表达数据文本的语义.文章提出了一个语义合成模型,该模型由领域本体、关键词语义抽取、概念语义相似度计算及语义推理等相关技术模型组成.文中对该模型进行了实验验证,通过对实验结果进行分析推理可知,文中提出的基于领域本体的语义合成模型提高了检索系统的查准率和计算机处理信息的能力,从而也提高了用户的满意度.     

基于模块抽取的大本体分块与映射

大本体规模过大,使得本体间映射复杂.针对已有方法在分块上的不足,提出一种基于模块抽取的大本体分块映射方法.通过建立本体依赖图的拉普拉斯矩阵来抽取本体模块,计算模块之间的相似度,实现分块映射.实验结果表明,该方法能有效实现大本体分块,提高映射效率.     

Contorsion: A Semantic XPath Processor

This work describes the architecture of Contorsion, a semantic XPath processor that acts over an RDF mapping of XML. It contributes to a recent research trend that defines an XML-to-RDF mapping allowing XML documents interoperate at the semantic level. We use a model-mapping approach to represent instances of XML and XML Schema in RDF. This representation retains the node order, in contrast with the usual structure-mapping approach. The processor can be fed with an unlimited set of XML schemas and/or RDFS/OWL ontologies. The queries are resolved taking in consideration the structural and semantic connections descrived in the schemas and ontologies. Such behaviour, schema-awareness and semantic integration, can be useful for exploiting schema and ontology hierarchies in XPath queries.     

Automated reasoning on UML conceptual schemas with derived information and queries

ContextIt is critical to ensure the quality of a software system in the initial stages of development, and several approaches have been proposed to ensure that a conceptual schema correctly describes the user’s requirements.ObjectiveThe main goal of this paper is to perform automated reasoning on UML schemas containing arbitrary constraints, derived roles, derived attributes and queries, all of which must be specified by OCL expressions.MethodThe UML/OCL schema is encoded in a first order logic formalisation, and an existing reasoning procedure is used to check whether the schema satisfies a set of desirable properties. Due to the undecidability of reasoning in highly expressive schemas, such as those considered here, we also provide a set of conditions that, if satisfied by the schema, ensure that all properties can be checked in a finite period of time.ResultsThis paper extends our previous work on reasoning on UML conceptual schemas with OCL constraints by considering derived attributes and roles that can participate in the definition of other constraints, queries and derivation rules. Queries formalised in OCL can also be validated to check their satisfiability and to detect possible equivalences between them. We also provide a set of conditions that ensure finite reasoning when they are satisfied by the schema under consideration.ConclusionThis approach improves upon previous work by allowing automated reasoning for more expressive UML/OCL conceptual schemas than those considered so far.     

Resolution of Semantic Heterogeneity in Database Schema Integration Using Formal Ontologies

This paper addresses the problem of handling semantic heterogeneity during database schema integration. We focus on the semantics of terms used as identifiers in schema definitions. Our solution does not rely on the names of the schema elements or the structure of the schemas. Instead, we utilize formal ontologies consisting of intensional definitions of terms represented in a logical language. The approach is based on similarity relations between intensional definitions in different ontologies. We present the definitions of similarity relations based on intensional definitions in formal ontologies. The extensional consequences of intensional relations are addressed. The paper shows how similarity relations are discovered by a reasoning system using a higher-level ontology. These similarity relations are then used to derive an integrated schema in two steps. First, we show how to use similarity relations to generate the class hierarchy of the global schema. Second, we explain how to enhance the class definitions with attributes. This approach reduces the cost of generating or re-generating global schemas for tightly-coupled federated databases.     

Automatic extraction of OWL ontologies from UML class diagrams: a semantics-preserving approach

Full implementation of the Semantic Web requires widespread availability of OWL ontologies. Manual ontology development using current OWL editors remains a tedious and cumbersome task that requires significant understanding of the new ontology language and can easily result in a knowledge acquisition bottleneck. On the other hand, abundant domain knowledge has been specified by existing database schemata such as UML class diagrams. Thus developing an automatic tool for extracting OWL ontologies from existing UML class diagrams is helpful to Web ontology development. In this paper we propose an automatic, semantics-preserving approach for extracting OWL ontologies from existing UML class diagrams. This approach establishes a precise conceptual correspondence between UML and OWL through a semantics-preserving schema translation algorithm. The experiments with our implemented prototype tool, UML2OWL, show that the proposed approach is effective and a fully automatic ontology extraction is achievable. The proposed approach and tool will facilitate the development of Web ontologies and the realization of semantic interoperations between existing Web database applications and the Semantic Web.     

Reasoning of fuzzy relational databases with fuzzy ontologies

A significant interest developed regarding the problem of describing databases with expressive knowledge representation techniques in recent years, so that database reasoning may be handled intelligently. Therefore, it is possible and meaningful to investigate how to reason on fuzzy relational databases (FRDBs) with fuzzy ontologies. In this paper, we first propose a formal approach and an automated tool for constructing fuzzy ontologies from FRDBs, and then we study how to reason on FRDBs with constructed fuzzy ontologies. First, we give their respective formal definitions of FRDBs and fuzzy Web Ontology Language (OWL) ontologies. On the basis of this, we propose a formal approach that can directly transform an FRDB (including its schema and data information) into a fuzzy OWL ontology (consisting of the fuzzy ontology structure and instance). Furthermore, following the proposed approach, we implement a prototype construction tool called FRDB2FOnto. Finally, based on the constructed fuzzy OWL ontologies, we investigate how to reason on FRDBs (e.g., consistency, satisfiability, subsumption, and redundancy) through the reasoning mechanism of fuzzy OWL ontologies, so that the reasoning of FRDBs may be done automatically by means of the existing fuzzy ontology reasoner.© 2012 Wiley Periodicals, Inc.     

一种概念本体的共享方案

针对不同知识系统概念和术语的不统一,讨论了应用领域知识系统在概念本体共享交换层的设计和实现,重点研究了本体在语法和语义上的异构性,提出了建立全局本体结合各本地本体系统的语义异构解决方案。在OIL对RDFS的扩展的基础上,依据框架概念本体表达的特点对RDFS进行了扩展补充,建立了概念本体与OIL及扩展RDF(S)语法的映射关系,确定了将概念本体转换为XML文本的方法。     

Identification and resolution of conflicts during ontological integration using rules

Abstract: Integration of ontologies of information sources and consumers is an important phase in achieving web‐based interoperability. The present work describes an approach for identifying certain semantic conflicts while integrating ontologies of heterogeneous information sources. This paper is focused on the identification of homonymy and synonymy between elements in ontologies. In the present work the concepts of homonymy and synonymy are synonymous to naming conflicts and entity identifier conflicts, respectively, and partial synonymy is synonymous to schema isomorphism conflicts. The concept of the mask of interoperability is introduced for the identification of synonymy. The mask of interoperability is expressed in a declarative way as a set of rules, which can then be used for resolution of conflicts during integration of ontologies. As proof of concept, ontologies are implemented using the XML‐based ontology language Ontology Web Language (OWL), and the rules are implemented using the emerging rule language Semantic Web Rule Language (SWRL). This representation in OWL and SWRL allows the ontology to be executable, flexibly extendable and platform‐independent. The OWL facts and SWRL rules are used by the Jess and Bossam reasoning engine to identify semantic homonymy and synonymy.