基于本体的XML语义集成研究

针对具有相同语义的XML数据经常具有不同表达形式的问题，采用了基于本体的语义集成方法来集成异构XML数据源，即通过一系列映射规则将XPath的局部路径与本体关联起来，将用户的RDQL查询重写为基于XML的XQuery查询，从而达到语义集成的效果。本方法的意义在于用户可以通过本体查询异构的XML数据源。     

基于本体的数据集成系统的设计与实现

针对当前对异构数据源的数据集成中存在的语义异构问题,尤其是元素层的语义异构,通过分析现有的基于XML数据集成方法的基础上,将系统的设计分为三层,其中在数据层实现对异构数据源XML模式的包装,而在用户层和数据层之间增加一个中间层来实现全局查询到局部查询的转换。同时将本体论的思想引入集成系统框架,通过在中间层建立全局本体库和局部本体库,以及构建本体库之间的映射关系,解决了数据集成中异构数据源元素层的语义异构问题。     

本体在XML信息源集成中的应用

提出了一种应用本体解决XML信息集成中语义异构的方案,设计了一个基于本体(Ontology)的XML信息集成框架。同时介绍了一种本体表示方法,并通过本体到XML Schema的映射算法,实现了对XML信息源语义层次上的有效性验证。最后阐述了XML信息查询算法,使用户可以通过本体方便地对异构XML信息源进行查询。     

一种基于本体的异构数据源模式集成

本体是概念模型的明确的规范说明,能够精确地描述概念体系和领域知识。为了将异构数据源中的数据识别出来并进行语义相关的集成,提出了一种基于本体集成异构数据源的方法。首先将各个数据源中的数据以XML文档形式进行描述,然后将各个XML文档的文档类型定义(DTD)转化为DIM数据模型表示,最后通过语义聚类、全局模式生成等步骤,实现XML文档的基于本体的语义集成。文中提出的方法以普林斯顿大学的心理学家、语言学家和计算机工程师联合设计的一种基于认知语言学的英语词典为本体库,可有效地识别出异构数据源中的具有等价语义或相近语义的数据,从而更准确地对异构数据源中的数据进行集成。     

一种基于本体的异构数据源模式集成

本体是概念模型的明确的规范说明,能够精确地描述概念体系和领域知识.为了将异构数据源中的数据识别出来并进行语义相关的集成,提出了一种基于本体集成异构数据源的方法.首先将各个数据源中的效据以XML文档形式进行描述,然后将各个XML文档的文档类型定义(DTD)转化为DIM数据模型表示,最后通过语义聚类、全局模式生成等步骤,实现XML文档的基于本体的语义集成.文中提出的方法以普林斯顿大学的心理学家、语言学家和计算机工程师联合设计的一种基于认知语言学的英语词典为本体库,可有效地识别出异构数据源中的具有等价语义或相近语义的数据,从而更准确地对异构数据源中的数据进行集成.     

异构专利数据源集成系统中查询的研究

为了有效地对异构专利数据源进行统一的查询,提出一个基于本体的异构专利数据源集成系统.该系统引入本体解决数据源集成中存在的语义异构,通过全局数据模式为用户提供统一的查询接口,将用户针对全局数据模式的查询重写为针对各个局部数据源的子查询.使用该系统,用户可以从异构的专利源中得到正确的查询结果.     

基于领域本体和关系模型的XML语义集成方法研究

由于缺乏足够的语义信息,不同模式的XML数据之间很难进行互操作。针对油气井工程中的XML数据集成需求,借助领域全局本体,提出一种模式无关的XML语义集成方法。该方法首先在XML Path路径与领域本体之间进行语义映射,屏蔽其模式差异;然后,按照模型映射方法将XML存储为关系数据;最后通过查询重写将SPARQL转换为SQL语句,实现语义查询。该方法对XML模式进行语义标注,利用关系数据库存储与查询XML数据,能有效处理领域XML数据的语义集成。     

基于本体的异构信息集成查询划分及转换

使用本体赋予信息语义能够帮助用户准确查询所需要的信息.基于本体的异构信息集成中的关键问题是如何实现全局本体概念实例查询到局域信息数据查询的变换.提出了一种本体概念实例查询的操作表示,并基于这一查询操作表示给出了将全局查询划分为局域查询的方法,局域查询结果经过集成和转换后以统一的形式返回给用户.使用该方法来查询所集成的数据来源,可以获取用户所需要的正确查询结果.     

一种基于Ontology的数据集成系统

针对异构数据源中实现基于语义的数据集成的需求，采用分层思想，在用户层与实际数据层之间增加一个中间层来屏蔽底层数据的异构，用本体作为公共语义描述工具，建立本体到各数据源的映射规则，设计实现了将基于本体的全局查询转化为基于各数据源的局部查询系统，解决了数据源之间的语义异构问题，其中用OWL表示本体和映射，并研究了系统中的关键技术。     

基于XML的异构数据源查询系统设计

XML语言因其具有与平台无关、易于扩展、数据描述性(语义性)强等特点,目前己经成为数据交换的标准,基于XML的数据查询技术研究成为当前研究的一个热点.在对异构数据集成关键技术的分析和研究的基础上,设计基于XML的异构数据源查询系统,为用户提供一个统一的数据集成平台以及优质、快速的信息资源共享服务,从数据集成的层面解决当前普遍存在的"信息孤岛"问题.     

基于本体的XML语义集成和查询的研究

XML因其结构上的灵活性和易扩展性已经成为Web上异构数据转换和传输的标准,但是含有不同模式的XML数据源之间却很难进行相互操作,这给XML数据检索带来了更大的不便.先提出一种从XML模式到OWL本体的映射算法,然后借助共享全局本体和同义词典实现多个映射后的本体在语义上的集成从而解决XML结构异构的问题,最后提出一种利用语义集成进行XML语义查询的框架并初步实现.     

基于本体的XML关联规则挖掘方法

针对传统的数据挖掘技术不能直接应用到半结构化的XML数据挖掘问题,给出了基于本体的XML关联规则挖掘方法。该方法引入领域本体和哈希技术来改进产生频繁项目集的操作和生成关联规则的操作,并且使用哈希表存储相关的领域本体,从而将数据库操作转化为对XML内存树的操作,通过理论分析和实验验证了方法的挖掘效果,论述了该方法的优点。     

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.     

SwetoDblp ontology of Computer Science publications

SwetoDblp is a large populated ontology with a shallow schema yet a large number of real-world instance data. We describe how such ontology is built from an XML source and how it can be maintained. Instead of a one-to-one mapping from XML to RDF, the creation of the ontology emphasizes the addition of relationships and the value of URIs. SwetoDblp is publicly available online. We also summarize research efforts that have used or are using this freely available community resource.     

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     

Constructing ontologies by mining deep semantics from XML Schemas and XML instance documents

With the development of the Semantic Web and Artificial Intelligence techniques, ontology has become a very powerful way of representing not only knowledge but also their semantics. Therefore, how to construct ontologies from existing data sources has become an important research topic. In this paper, an approach for constructing ontologies by mining deep semantics from eXtensible Markup Language (XML) Schemas (including XML Schema 1.0 and XML Schema 1.1) and XML instance documents is proposed. Given an XML Schema and its corresponding XML instance document, 34 rules are first defined to mine deep semantics from the XML Schema. The mined semantics is formally stored in an intermediate conceptual model and then is used to generate an ontology at the conceptual level. Further, an ontology population approach at the instance level based on the XML instance document is proposed. Now, a complete ontology is formed. Also, some corresponding core algorithms are provided. Finally, a prototype system is implemented, which can automatically generate ontologies from XML Schemas and populate ontologies from XML instance documents. The paper also classifies and summarizes the existing work and makes a detailed comparison. Case studies on real XML data sets verify the effectiveness of the approach.     

Fuzzy semantic tagging and flexible querying of XML documents extracted from the Web

The relational database model is widely used in real applications. We propose a way of complementing such a database with an XML data warehouse. The approach we propose is generic, and driven by a domain ontology. The XML data warehouse is built from data extracted from the Web, which are semantically tagged using terms belonging to the domain ontology. The semantic tagging is fuzzy, since, instead of tagging the values of the Web document with one value of the domain ontology, we propose to use tags expressed in terms of a possibility distribution representing a set of possible terms, each term being weighted by a possibility degree. The querying of the XML data warehouse is also fuzzy: the end-users can express their preferences by means of fuzzy selection criteria. We present our approach on a first application domain: predictive microbiology.     

一种基于Ontology的XML Schema复用方法

随着企业的发展,企业往往面临成百上千的XML Schema文档。XML Schema中存在的冗余和重复的问题已经不容忽视。本文首先讨论了利用本体来描述XML Schema语义的可能性,随后给出了一种基于本体的XML Schema复用方法,最后用一个具体的例子说明该方法的过程。     

Extracting knowledge from XML document repository: a semantic Web-based approach

XML plays an important role as the standard language for representing structured data for the traditional Web, and hence many Web-based knowledge management repositories store data and documents in XML. If semantics about the data are formally represented in an ontology, then it is possible to extract knowledge: This is done as ontology definitions and axioms are applied to XML data to automatically infer knowledge that is not explicitly represented in the repository. Ontologies also play a central role in realizing the burgeoning vision of the semantic Web, wherein data will be more sharable because their semantics will be represented in Web-accessible ontologies. In this paper, we demonstrate how an ontology can be used to extract knowledge from an exemplar XML repository of Shakespeare’s plays. We then implement an architecture for this ontology using de facto languages of the semantic Web including OWL and RuleML, thus preparing the ontology for use in data sharing. It has been predicted that the early adopters of the semantic Web will develop ontologies that leverage XML, provide intra-organizational value such as knowledge extraction capabilities that are irrespective of the semantic Web, and have the potential for inter-organizational data sharing over the semantic Web. The contribution of our proof-of-concept application, KROX, is that it serves as a blueprint for other ontology developers who believe that the growth of the semantic Web will unfold in this manner.