一种基于文档内容的语义标注方法

互联网上存在海量数据,如何在大量的信息中查找到有用信息就变成了一个至关重要的问题。语义网为解决这一问题带来了曙光。然而当今网络现状与语义网之间存在巨大差距,即海量非结构化的页面内容难直接转化为语义的知识。提出了一种基于文档内容的语义标注方法,利用本体所表达的语义环境,即本体知识相关词汇及其所处的语义上下文环境在文档中出现频率,实现对文档的语义标注。实验显示方法取得良好的效果,但受本体知识质量和标注文档质量两个因素影响较大。     

基于本体的Web使用知识发现模型及应用

本体在Web上的应用能够有效解决Web信息共享的语义问题。该文提出了基于Web本体和服务器日志文件的知识发现模型，主要讨论了用户访问行为的表示、语义用户分布的定义及发现算法。最后介绍了Web使用知识发现模型在Web个性化系统中的应用。     

语义网服务中的本体集成框架

分析语义网服务中存在的各种本体异构,明确语义网服务中本体集成的主要研究方向.在此基础上,提出一个语义网服务模型下的本体集成框架,讨论其中数据层中介器和Web服务中介器的结构并阐明其工作机制,为全面解决语义网服务环境下的本体集成问题提供了一种新的思路.     

语义万维网中基于Agent的智能检索框架

语义万维网是目前国际万维网联盟（world wide web consortium,W3C）为了解决因Web上的数据缺少语义信息而难以实现自动化处理的问题所开展的研究项目,其目的是为了对Web上发布的信息实现智能推理和自动化处理。Agent作为一种智能化主体,非常适合语义万维网环境下的各种应用。在语义万维网和智能Agent研究的基础上,综合信息检索、知识表示、Ontology建模等多方面技术,提出并实现了一个基于Ontology实现语义信息检索的多Agent系统框架,该系统包括信息收集、存储、查询和推理4个主要部分。     

基于本体的企业网络知识管理系统的构建与实现

提出了运用本体构造企业网络知识管理系统模型的方法。本方法克服了原有相关系统存在的固有不足,从面向对象的角度探讨了构造企业网络知识管理系统的可能性。以此为基础,重点讨论了基于本体的企业网络知识管理系统构建方法。最后设计了一个企业网络知识管理实验系统,并给出了具体实例。     

BiOSS: A system for biomedical ontology selection

In biomedical informatics, ontologies are considered a key technology for annotating, retrieving and sharing the huge volume of publicly available data. Due to the increasing amount, complexity and variety of existing biomedical ontologies, choosing the ones to be used in a semantic annotation problem or to design a specific application is a difficult task. As a consequence, the design of approaches and tools addressed to facilitate the selection of biomedical ontologies is becoming a priority. In this paper we present BiOSS, a novel system for the selection of biomedical ontologies. BiOSS evaluates the adequacy of an ontology to a given domain according to three different criteria: (1) the extent to which the ontology covers the domain; (2) the semantic richness of the ontology in the domain; (3) the popularity of the ontology in the biomedical community. BiOSS has been applied to 5 representative problems of ontology selection. It also has been compared to existing methods and tools. Results are promising and show the usefulness of BiOSS to solve real-world ontology selection problems. BiOSS is openly available both as a web tool and a web service.     

面向装配序列规划的装配本体设计*

为提高装配序列规划的自动化程度,实现装配相关活动间信息的共享、重用和顺畅传递,实现装配序列规划系统与其它异构系统之间的无缝集成和互操作,将本体技术引入到装配建模中.针对装配序列规划建模需求,构建面向装配序列规划且基于装配对象的装配本体(OWL-ASP).OWL-ASP由Properties本体、AssemblyInfo本体和AssemblySeq本体组成,分别描述装配对象的装配属性、装配信息、装配顺序等.在OWL-ASP的基础上,利用语义Web规则语言刻画装配规则,形成统一的装配知识表示层次体系,实现对装配知识的严格刻画和自动推理.通过球阀装配的实例说明装配本体和装配规则的有效性.     

流程可定制本体匹配框架:RiMOM2

本体作为语义Web中的语义表示形式,是语义Web体系结构中的核心元素,是实现知识共享、协同工作的关键。然而现实世界中本体自身与生俱来的分布性和异构性,又极大地限制了数据的共享与集成。为了实现知识的共享、数据的集成,近年来针对本体匹配方法的研究得到了广泛的重视。随着本体匹配研究的深入,许多有效的本体匹配方法被提出。RiMOM2正是一种集成了多种有效本体匹配方法的多策略本体匹配框架。它尽可能地向初级用户隐藏不必要的阂值设定和参数设置,而向高级用户提供匹配流程的可定制功能,以期针对不同用户实现一种既能适用于普遍本体匹配任务,操作简易,又能达到具有针对性匹配效果的本体匹配工具。同时该框架具有匹配方法组件的易扩展性。     

面向结构健康评估网格的语义信息服务模型

为了更好地支持网格环境下的结构健康评估服务管理,结合本体和语义Web技术,提出了面向结构健康评估网格的语义信息服务模型。重点探讨了结构健康评估本体、结构健康评估网格服务本体和语义服务匹配方法的构建。基于该模型构建的语义信息服务组件已成功应用于洞庭湖大桥的结构健康评估网格系统中。     

A Methodology to Create Legal Ontologies in a Logic Programming Based Web Information Retrieval System

Web legal information retrieval systems need the capability to reason with the knowledge modeled by legal ontologies. Using this knowledge it is possible to represent and to make inferences about the semantic content of legal documents. In this paper a methodology for applying NLP techniques to automatically create a legal ontology is proposed. The ontology is defined in the OWL semantic web language and it is used in a logic programming framework, EVOLP+ISCO, to allow users to query the semantic content of the documents. ISCO allows an easy and efficient integration of declarative, object-oriented and constraint-based programming techniques with the capability to create connections with external databases. EVOLP is a dynamic logic programming framework allowing the definition of rules for actions and events. An application of the proposed methodology to the legal web information retrieval system of the Portuguese Attorney General’s Office is described.     

基于领域学习的本体映射方法

在语义数据集成中本体映射是关键,手工设置映射关系不仅消耗时间而且不准确,需要使用本体映射工具自动发现这种映射关系.在现有本体映射方法的基础上提出了基于领域学习的映射发现策略,可以从领域知识中发现复杂映射的规则,增加映射时的实例数据,从而提高映射发现的查全率和准确率;同时利用本体中丰富的语义知识去筛选候选数据,从而降低映射方法的算法复杂度.实验证明该方法是有效的.     

Building Ontology for Different Emotional Contexts and Multilingual Environment in Opinion Mining

With the explosive growth of various social media applications, individuals and organizations are increasingly using their contents (e.g. reviews, forum discussions, blogs, micro-blogs, comments, and postings in social network sites) for decision-making. These contents are typical big data. Opinion mining or sentiment analysis focuses on how to extract emotional semantics from these big data to help users to get a better decision. That is not an easy task, because it faces many problems, such as different context may make the meaning of the same word change variously, at the same time multilingual environment restricts the full use of the analysis results. Ontology provides knowledge about specific domains that are understandable by both the computers and developers. Building ontology is mainly a useful first step in providing and formalizing the semantics of information representation. We proposed an ontology DEMLOnto based on six basic emotions to help users to share existed information. The ontology DEMLOnto would help in identifying the opinion features associated with the contextual environment, which may change along with applications. We built the ontology according to ontology engineering. It was developed on the platform Protégé by using OWL2.     

一种本体知识文摘方法的研究和实现

本体作为领域知识的表示方法，已经成为语义Web的基础。本体通常由领域专家建立，用于表示领域中概念以及概念与概念之间的关系。但这也使得普通用户难以理解本体中描述的信息。普通用户往往希望本体中的信息能够以自然语言的形式描述。这正是本文讨论的主要问题。本文采用分治策略，利用基于嵌套复杂模板的解决方案，设计并实现了本体知识文摘的算法。我们开发了一个原型系统SWARMS，并将该文摘算法进行了运用。初步的实验表明，本文提出的方法取得较好的结果。     

故障树领域本体及SWRL规则的构建方法研究

故障树(Fault Tree,FT)被广泛应用于系统故障的快速定位,但其因缺乏精确的语义信息而存在重复构建问题。将本体引入到故障树领域中,并对如何构建故障树本体及相应的SWRL规则进行了研究:首先采用本体描述语言 (Web Ontology Language,OWL)对故障树中的概念及概念之间的关系进行知识表示,构建了一个可共享、可重用、可扩展的故障树领域本体;然后将故障树中事件之间的逻辑关系转化成语义 Web 规则语言 (Semantic Web Rule Language,SWRL);最后将构建的故障树领域本体和SWRL规则放入JESS推理机中进行推理,产生新的知识,用于系统故障的快速定位。实验证明,使用所提出的方法能在解决故障树重复构建问题的同时,不对系统故障的快速定位产生影响。     

基于Ontology的建模方法

Ontology作为一种描述概念与概念之间关系的模型,能够解决知识共享和重用问题,近年来已被广泛应用于计算机科学的众多领域中,如数字图书馆、软件复用、Web异构信息的处理和语义Web等.介绍了Ontology的定义、分类及组成,并且介绍了建立本体的步骤,通过一个具体的实例详细阐述了建立本体的过程,最后给出了建立本体的构造图.     

基于本体的电力信息系统的语义集成研究

在语义网以及OWL等本体技术的基础上，构建了一种新型的信息集成系统（EOSIS）来实现电力企业信息的集成、语义连接及推理。其中包括EOSIS的业务需求分析、集成策略以及系统结构。EOSIS不同与现有的集成系统之处在于，它可以支持支持概念和对象的多维查询及导航、隐含业务信息推理、领域概念、事实的动态增加等功能。     

基于本体的分布式实例推理技术研究

为了克服单一实例库知识的局限性,实现分布式环境下多数据源的知识重用和共享,提出了一个分布式实例推理系统框架.系统通过本体服务器建立和维护实例库之间的本体知识,其中基本本体为知识的表示提供了全局约束和基础,实例推理服务器可以在基本本体框架下定义领域本体来灵活表达各自的领域知识,而本体目录则为知识的检索提供了向导.本体的引入解决了不同实例库之间知识的互理解和互操作性,能够有效地实现多实例库的协同推理.系统采用Web Service技术构建,是一个开放的系统框架,具有很强的可扩展性.     

SweetWiki: A semantic wiki

Everyone agrees that user interactions and social networks are among the cornerstones of “Web 2.0”. Web 2.0 applications generally run in a web browser, propose dynamic content with rich user interfaces, offer means to easily add or edit content of the web site they belong to and present social network aspects. Well-known applications that have helped spread Web 2.0 are blogs, wikis, and image/video sharing sites; they have dramatically increased sharing and participation among web users. It is possible to build knowledge using tools that can help analyze users’ behavior behind the scenes: what they do, what they know, what they want. Tools that help share this knowledge across a network, and that can reason on that knowledge, will lead to users who can better use the knowledge available, i.e., to smarter users. Wikipedia, a wildly successful example of web technology, has helped knowledge-sharing between people by letting individuals freely create and modify its content. But Wikipedia is designed for people—today's software cannot understand and reason on Wikipedia's content. In parallel, the “semantic web”, a set of technologies that help knowledge-sharing across the web between different applications, is starting to gain attraction. Researchers have only recently started working on the concept of a “semantic wiki”, mixing the advantages of the wiki and the technologies of the semantic web. In this paper we will present a state-of-the-art of semantic wikis, and we will introduce SweetWiki, an example of an application reconciling two trends of the future web: a semantically augmented web and a web of social applications where every user is an active provider as well as a consumer of information. SweetWiki makes heavy use of semantic web concepts and languages, and demonstrates how the use of such paradigms can improve navigation, search, and usability.     

一种本体概念的语义相似度计算方法

概念语义相似度已广泛应用于 Web 服务发现、本体映射等领域, 但现有的概念语义相似度计算方法对概念间语义相似程度的区分不够细致. 本文从本体结构出发, 首先提出了自底向上的本体概念出现概率计算方法, 并在此基础上改进了基于节点信息量的概念语义相似性度量方法; 然后又设计了基于边计算的本体概念语义相似度计算方法; 最后对上述两种方法线性加权, 提出了一种加权的本体概念语义相似度计算方法. 实验结果表明该方法能进一步正确区分本体中父子概念及兄弟概念间的相似程度.