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.     

A formal approach for graphically building fuzzy XML model

eXtensible Markup Language (XML) has been the de facto standard of data representation and exchange over the Web. In addition, imprecise and uncertain data are inherent in the real world. Although fuzzy data have been extensively investigated in the context of the relational model, the classical relational database model and its fuzzy extension to date do not satisfy the need of modeling complex objects with imprecision and uncertainty on the Web. On the basis of possibility theory, this paper concentrates on fuzzy information modeling in the fuzzy XML model and the fuzzy IFO model. In particular, the formal approach to mapping a fuzzy IFO model to a fuzzy document-type definition model is developed.     

Automatic fuzzy ontology generation for semantic Web

Ontology is an effective conceptualism commonly used for the semantic Web. Fuzzy logic can be incorporated to ontology to represent uncertainty information. Typically, fuzzy ontology is generated from a predefined concept hierarchy. However, to construct a concept hierarchy for a certain domain can be a difficult and tedious task. To tackle this problem, this paper proposes the FOGA (fuzzy ontology generation framework) for automatic generation of fuzzy ontology on uncertainty information. The FOGA framework comprises the following components: fuzzy formal concept analysis, concept hierarchy generation, and fuzzy ontology generation. We also discuss approximating reasoning for incremental enrichment of the ontology with new upcoming data. Finally, a fuzzy-based technique for integrating other attributes of database to the ontology is proposed.     

基于数据挖掘的煤矿安全信息管理模型的研究

基于对数据挖掘技术、粗糙集理论、模糊逻辑与神经网络算法的分析,文章提出了一种基于数据挖掘的煤矿安全信息管理模型的设计方案。该模型应用Web服务器注册技术和XML数据合成技术形成终端数据库,采用数据挖掘技术中的粗糙集理论和模糊逻辑与神经网络算法形成终端数据仓库,并对终端数据仓库进行统一分析、管理和维护,有效地提高了煤矿安全信息管理的效率。     

Representing and Reasoning About XML with Ontologies

The eXtensible Markup Language (XML) has reached a wide acceptance as the relevant standardization for representing and exchanging data on the Web. Unfortunately, XML covers the syntactic level but lacks semantics, and thus cannot be directly used for the Semantic Web. Currently, finding a way to utilize XML data for the Semantic Web is challenging research. As we have known that ontology can formally represent shared domain knowledge and enable semantics interoperability. Therefore, in this paper, we investigate how to represent and reason about XML with ontologies. Firstly, we give formalized representations of XML data sources, including Document Type Definitions (DTDs), XML Schemas, and XML documents. On this basis, we propose formal approaches for transforming the XML data sources into ontologies, and we also discuss the correctness of the transformations and provide several transformation examples. Furthermore, following the proposed approaches, we implement a prototype tool that can automatically transform XML into ontologies. Finally, we apply the transformed ontologies for reasoning about XML, so that some reasoning problems of XML may be checked by the existing ontology reasoners.     

一种模糊XML模型的概念设计方法

XML(Extensible Markup Language)已经成为Web上数据表示与交换的标准,而信息的不精确性和不确定性又广泛存在于现实世界应用中。虽然模糊信息在关系数据库框架下已经被广泛讨论,但是传统的关系数据库模型及其模糊扩展形式不能满足表示和处理Web上复杂模糊对象的需要。基于可能性分布,研究在XML模型和IFO数 据模型—一种概念数据模型中进行模糊信息建模,给出把模糊IFO数据模型映射成模糊XML DTD模型的形式化方法。     

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.     

DOF: a generic approach of domain ontology fuzzification

Although recent studies on the Semantic Web have focused on crisp ontologies and knowledge representation, they have paid less attention to imprecise knowledge. However, the results of these studies constitute a Semantic Web that can answer requests almost perfectly with respect to precision. Nevertheless, they ensure low recall. As such, we propose in this research work a new generic approach of fuzzification that which allows a semantic representation of crisp and fuzzy data in a domain ontology. In the framework of our real case study, the obtained illustrate that our approach is highly better than the crisp one in terms of completeness, comprehensiveness, generality, comprehension and shareability.     

The Semantic Web: the roles of XML and RDF

XML and RDF are the current standards for establishing semantic interoperability on the Web, but XML addresses only document structure. RDF better facilitates interoperation because it provides a data model that can be extended to address sophisticated ontology representation techniques. We explain the role of ontologies in the architecture of the Semantic Web. We then briefly summarize key elements of XML and RDF, showing why using XML as a tool for semantic interoperability will be ineffective in the long run. We argue that a further representation and inference layer is needed on top of the Web's current layers, and to establish such a layer, we propose a general method for encoding ontology representation languages into RDF/RDF schema. We illustrate the extension method by applying it to Ontology Interchange Language, an ontology representation and inference language     

集成Web 数据的系统框架与实现方法

基于我们正在研究和开发的项目Panorama，本文提出了一个基于XML和CORBA的Web数据集成系统框架，该框架可以集成来自Web上多个异构的数据源，包括关系数据库、面向对象数据库,HTML和XML文档及结构化文本文件。在系统实现中，把Web看作是一个巨大的虚拟数据库，以CORBA作为分布式对象模型，以XML作为公共誓据模型，并且以XML-QL作为全局查询语言来完成Web上的数据查询和集成。文中还详细分析和描述了系统框架中的一些主要模块的实现方法，具有很好的可操作性。     

Fuzzy XML data modeling with the UML and relational data models

Information imprecision and uncertainty exist in many real-world applications and for this reason fuzzy data modeling has been extensively investigated in various data models. Currently, huge amounts of electronic data are available on the Internet, and XML has been the de facto standard of information representation and exchange over the Web. This paper focuses on fuzzy XML data modeling, which is mainly involved in the representation model of the fuzzy XML, its conceptual design, and its storage in databases. Based on “possibility distribution theory”, we developed this fuzzy XML data model. We developed this fuzzy UML data model to design the fuzzy XML model conceptually. We investigated the formal conversions from the fuzzy UML model to the fuzzy XML model and the formal mapping from the fuzzy XML model to the fuzzy relational databases.     

领域本体方法在数据仓库元数据管理中的应用研究*

提出一个利用领域本体解决数据仓库元数据管理中的语义异构问题的方法,即在局部元数据与领域本体之间建立映射,利用领域本体对局部元数据进行语义集成。最后,在医疗领域数据仓库项目建设中,进行了实验数据分析。结果表明,领域本体方法可以有效地集成数据仓库应用中不同业务部门的异构数据。     

A weighted common structure based clustering technique for XML documents

XML has recently become very popular as a means of representing semistructured data and as a standard for data exchange over the Web, because of its varied applicability in numerous applications. Therefore, XML documents constitute an important data mining domain. In this paper, we propose a new method of XML document clustering by a global criterion function, considering the weight of common structures. Our approach initially extracts representative structures of frequent patterns from schemaless XML documents using a sequential pattern mining algorithm. Then, we perform clustering of an XML document by the weight of common structures, without a measure of pairwise similarity, assuming that an XML document is a transaction and frequent structures extracted from documents are items of the transaction. We conducted experiments to compare our method with previous methods. The experimental results show the effectiveness of our approach.     

XML技术在化学深层网数据提取中的应用

Internet上的化学数据库是宝贵的化学信息资源,如何有效地利用这些数据是化学深层网所要解决的问题。本文总结了化学深层网的特点,基于XML技术实现从数据库检索返回的半结构化HTML页面中提取数据的目标,使之成为可供程序直接调用做进一步计算的数据。在数据提取过程中,先采用JTidy规范化HTML,得到格式上完整、内容无误的XHTML文档,利用包含着XPath路径语言的XSLT数据转换模板实现数据转换和提取。其中XPath表达式的优劣决定了XSLT数据转换模板能否长久有效地提取化学数据,文中着重介绍了如何编辑健壮的XPath表达式,强调了XPath表达式应利用内容和属性特征实现对源树中数据的定位,并尽可能地降低表达式之间的耦合度,前瞻性地预测化学站点可能出现的变化并在XSLT数据转换模板中采取相应的措施以提高表达式的长期有效性。为创建化学深层网数据提取的XSLT数据提取模板提供方法指导。     

Constraint Preserving Transformation from Relational Schema to XML Schema

XML has become the standard for publishing and exchanging data on the Web. However, most business data is managed and will remain to be managed by relational database management systems. As such, there is an increasing need to efficiently and accurately publish relational data as XML documents for Internet-based applications. One way to publish relational data is to provide virtual XML documents for relational data via an XML schema which is transformed from the underlying relational database schema such that users can access the relational database through the XML schema. In this paper, we discuss issues in transforming a relational database schema into the corresponding XML schema. We aim to preserve all integrity constraints defined in a relational database schema, to achieve high level of nesting and to avoid introducing data redundancy in the transformed XML schema. In the paper, we first propose a basic transformation algorithm which introduces no data redundancy, then we improve the algorithm by exploring further nesting of the transformed XML schema.     

基于SWMVR的视频考勤系统应用研究*

随着语义Web技术的不断发展，基于XML的数据文档管理成为语义Web技术发展的难题，特别是RDF，DAML，OIL，OWL等本体语言的提出，基于XML的本体文档日趋复杂，传统的在关系数据库中依靠映射关系管理本体文档越来越困难。提出使用XML数据库Xindice来存储查询本体文档并设计了存储查询方法。     

Active XML-based Web data integration

Today, the Web is the largest source of information worldwide. There is currently a strong trend for decision-making applications such as Data Warehousing (DW) and Business Intelligence (BI) to move onto the Web, especially in the cloud. Integrating data into DW/BI applications is a critical and time-consuming task. To make better decisions in DW/BI applications, next generation data integration poses new requirements to data integration systems, over those posed by traditional data integration. In this paper, we propose a generic, metadata-based, service-oriented, and event-driven approach for integrating Web data timely and autonomously. Beside handling data heterogeneity, distribution and interoperability, our approach satisfies near real-time requirements and realize active data integration. For this sake, we design and develop a framework that utilizes Web standards (e.g., XML and Web services) for tackling data heterogeneity, distribution and interoperability issues. Moreover, our framework utilizes Active XML (AXML) to warehouse passive data as well as services to integrate active and dynamic data on-the-fly. AXML embedded services and changes detection services ensure near real-time data integration. Furthermore, the idea of integrating Web data actively and autonomously revolves around mining events logged by the data integration environment. Therefore, we propose an incremental XML-based algorithm for mining association rules from logged events. Then, we define active rules dynamically upon mined data to automate and reactivate integration tasks. Finally, as a proof of concept, we implement a framework prototype as a Web application using open-source tools.     

Formal translation from fuzzy EER model to fuzzy XML model

XML has been the de facto standard of data representation and exchange over the Web. In addition, fuzzy data are inherent in the real-world applications. Although fuzzy information has been extensively investigated in the context of relational database model, the classical relational database model and its fuzzy extension to date do not satisfy the need of modeling and processing complex objects with imprecision and uncertainty on the Web. Based on fuzzy sets, this paper concentrates on fuzzy information modeling in the EER (enhanced entity-relationship or extended entity-relationship) model and the fuzzy XML model. In particular, the formal approach to mapping the fuzzy EER model to the fuzzy DTD (document type definition) model is developed.     

Fuzzy data modeling and algebraic operations in XML

XML has been the de‐facto standard of information representation and exchange over the web. As the next generation of the Web language, XML is straightforwardly usable over the Internet. At the same time, the real world is filled with imprecision and uncertainty. However, the existed works fall short in their ability to model imprecise and uncertain data using XML. In this paper, we propose a new fuzzy XML data model based on XML Schema. With the model used, the fuzzy information in XML documents can be represented naturally. Along with the model, an associated algebra is presented formally. We also introduce how to use our algebra to capture queries expressed in XQuery. It shows that this model and algebra can establish a firm foundation for publishing and managing the histories of fuzzy data on the Web. © 2010 Wiley Periodicals, Inc.