模糊OWL 2本体到模糊关系数据库映射形式化方法

针对语义Web上的模糊OWL 2本体,提出了基于关系数据库的模糊本体存储方法.通过深入分析模糊OWL 2本体的结构及语义特点,提出了基于模糊关系数据库的模糊本体存储结构,在此基础上,给出了模糊OWL 2本体到模糊关系数据库映射的形式化方法.理论和实例结果表明所提出的形式化映射方法是合理和可行的.

语义Web本体语言OWL2研究

语义网因具有对网络空间所储存的数据进行智能评估的能力,使其从诞生之日起便成为计算机研究的热点领域。OWL2是一个本体语言,用于带有形式化定义含义的语义网。本文是对OWL2 Web本体语言新特性的介绍,同时包含了对OWL2与OWL初始版本之间不同点的解释,也介绍了激发设计主要新特性的需求,并从理论和实现的角度阐述了这些新特性的原理。

ORM模型转换为OWL2公理的映射规则

对象角色建模方法ORM目前已发展成为一种本体工程方法。需要将ORM表达的领域知识发布到语义Web上,以供不同应用系统共享和交换。OWL2是W3C推荐使用的语义Web本体语言。探讨了将ORM模型映射为OWL2公理的方法,通过模型等价变换和引入新的公理,给出了所有可行的模型映射规则。

基于ORM的OWL2本体可视化表达

无相关技术背景的领域专家较难直接阅读和理解OWL 2本体。为此,提出一种使用对象角色建模(ORM)可视化表达OWL 2本体的方法,并介绍一系列相应规则。通过语义等价的模型变换和扩展构造原语,使用ORM可视化表达OWL 2的构造原语、类表达式、类公理、对象特性公理、数据特性公理和键公理。实验结果表明,内置数据类型、类等价公理和对象特性的传递性公理需要对ORM进行扩展才能表达,其余OWL 2类和公理均可语义无损地转换为ORM模型。

SNOMED CT: A Clinical Terminology but Also a Formal Ontology

Context and Objective: Over the past few decades, terminologies developed for clinical descriptions have been increasingly used as key resources for knowledge management, data integration, and decision support to the extent that today they have become essential in the biomedical and health field. Among these clinical terminologies, some may possess the characteristics of one or several types of representation. This is the case for the Systematized Nomenclature of Human and Veterinary Medicine—Clinical Terms (SNOMED CT), which is both a clinical medical terminology and a formal ontology based on the principles of semantic web. Methods: We present and discuss, on one hand, the compliance of SNOMED CT with the requirements of a reference clinical terminology and, on the other hand, the specifications of the features and constructions of descriptive of SNOMED CT. Results: We demonstrate the consistency of the reference clinical terminology SNOMED CT with the principles stated in James J. Cimino’s desiderata and we also show that SNOMED CT contains an ontology based on the EL profile of OWL2 with some simplifications. Conclusions: The duality of SNOMED CT shown is crucial for understanding the versatility, depth, and scope in the health field.

基于多头自注意力模型的本体匹配方法

随着语义网的发展,本体数量不断增加,本体间的语义关系变得越来越复杂。因此,引入OWL2Vec*方法获取本体的语义嵌入表示。通常,匹配的类或属性具有相似的结构,因此利用了字符级和结构级的相似性度量。为高效融合多种相似度值,提出基于多头自注意力模型的本体匹配方法(Ontology Matching Method Based on Multi-Head Self-Attention, OM-MHSA)自主学习各相似度方法对匹配结果的贡献值。在国际本体对齐评测组织(Ontology Alignment Evaluation Initiative, OAEI)提供的Conference数据集上进行实验,结果表明,相对LSMatch和KGMatcher+方法,提出的模型准确率(Precision)提升了6%,召回率(Recall)和F1值(F1-measure)超过了ALIOn、TOMATO和Matcha等方法。可见,提出的模型能够提升匹配结果的效率。

基于本体的农产品供应链知识表示与推理研究

以Protégé4.3为本体编辑工具,运用OWL2语言对农产品供应链本体概念进行定义和形式化表达,探讨农产品供应链本体构建过程。

τSQWRL:A TSQL2-Like Query Language for Temporal Ontologies Generated from JSON Big Data

Temporal ontologies allow to represent not only concepts,their properties,and their relationships,but also time-varying information through explicit versioning of definitions or through the four-dimensional perdurantist view.They are widely used to formally represent temporal data semantics in several applications belonging to different fields(e.g.,Semantic Web,expert systems,knowledge bases,big data,and artificial intelligence).They facilitate temporal knowledge representation and discovery,with the support of temporal data querying and reasoning.However,there is no standard or consensual temporal ontology query language.In a previous work,we have proposed an approach namedτJOWL(temporal OWL 2 from temporal JSON,where OWL 2 stands for"OWL 2 Web Ontology Language"and JSON stands for"JavaScript Object Notation").τJOWL allows(1)to automatically build a temporal OWL 2 ontology of data,following the Closed World Assumption(CWA),from temporal JSON-based big data,and(2)to manage its incremental maintenance accommodating their evolution,in a temporal and multi-schema-version environment.In this paper,we propose a temporal ontology query language forτJOWL,namedτSQWRL(temporal SQWRL),designed as a temporal extension of the ontology query language—Semantic Query-enhanced Web Rule Language(SQWRL).The new language has been inspired by the features of the consensual temporal query language TSQL2(Temporal SQL2),well known in the temporal(relational)database community.The aim of the proposal is to enable and simplify the task of retrieving any desired ontology version or of specifying any(complex)temporal query on time-varying ontologies generated from time-varying big data.Some examples,in the Internet of Healthcare Things(IoHT)domain,are provided to motivate and illustrate our proposal.

中文高受控词表的OntoThesaurus描述规范

针对中文叙词表等高受控词表的描述需求以及向细粒度本体的演化趋势,在已有中文叙词表本体研究成果的基础上,基于OWL DL和OWL2研究制定高受控词表的OntoThesaurus描述规范,确定独立的命名域及其缩写以及一整套严格的形式化定义。根据语义Web的应用环境,编写OntoThesaurus的RDF Schema,以RDF/XML语法的方式向机器用户提供其中的类和属性的使用。说明OntoThesaurus不同于SKOS和CNKOS的特殊定义,给出描述示例以及三者之间的词汇对应关系。最后简单介绍OntoThesaurus支持系统的功能。