Web资源质量元数据度量方法研究

该文针对web信息资源描述现状,将web资源／4-8息质量评测模型WebQM理解为web资源质量元数据模型。按照都柏林核心元数据集DC规范,使用DC元数据对网络资源进行描述,将质量元模型中质量评价准则映射为相对应的质量元数据。并讨论了如何使用质量元数据对质量准则进行度量。     

基于Web信息组织模型的元数据检索技术

针对目前互联网搜索引擎主要使用全文检索技术,无法从Web页面中提取元数据信息情况,设计了一个基于信息组织模型的Web元数据信息提取和检索系统.使用基于正则表达式的元数据信息提取模型,信息提取和索引程序不断从数量巨大的Web页面中提取元数据信息,对本地元数据库进行不断地更新.抽象了多种Web信息组织模型,设计了相应的信息检索模型,并且这些模型可以大范围地应用于提取Web站点的元数据,所采用的方法充分利用了Web页面的数据结构,避免了采用复杂的语法、语义分析,为面向多个领域的元数据信息检索做出了一定的研究和探索.     

基于本体论相互属性的Web资源元数据模型

要使Web资源支持资源的自动发现，首先需要对Web资源提供必要的描述。Web资源的元数据模型——资源描述框架只能表示资源之间的二元关系，多元关系必须转化为二元关系后才能表示。然而多元关系与其转化为多个二元关系后所具有的语义是不相同的。针对资源描述框架存在的上述问题，该文引入本体论相互属性的概念，避免了不恰当地使用多个二元关系表示多元关系。同时给出了Web资源元数据本体模型的XML标记库，使得描述Web资源的本体模型可以在Web网络上传输，并被搜索引擎解析和理解。     

面向语义的元数据模型及OWL表示

元数据在国内依然是一个研究热点。本文面向基于语义的信息资源共享，就如何利用人工智能领域内的本体理论，建立用于描述信息资源语义及其之间关系的元数据模型进行了研究；基于给出的元数据模型声明了一个具体的学校实例，并使用OWL语言对其进行描述；初步实现了基于元数据模型的信息资源元数据描述模版和描述工具原型。     

面向Web服务的空间元数据管理研究

空间元数据系统是网络环境下解决空间信息共享的主要途径之一,本文探讨了空间元数据管理过程中所涉及的一些标准和技术,同时针对分布式Web环境下的空间数据信息,提出基于全局空间元数据库中心,分层多级的元数据管理方法.目前的元数据标准描述缺少服务信息的描述,本文对元数据描述信息进行了扩展,在管理系统中增加元数据服务,使之能在UDDI中发布服务,实现空间数据服务的发现.并在此基础上对分布式Web环境下的空间元数据管理系统的实现进行了初步探索.     

基于元数据构建自描述的Web应用框架

在Web应用系统中,具有自适应能力的Web应用框架将极大地提高系统的开发、部署和维护效率。基于元数据的表征能力,扩展了MVC设计模式,建立模型元数据、视图元数据、控制元数据,分别对系统中模型、视图和控制进行详细地描述,并利用应用程序元数据对三类元数据之间的关系进行描述,在此基础上,构建了一个自描述的、具有良好自适应性和可扩充性的Web应用框架。     

基于元数据的国土资源共享模型研究与设计

国土资源数据是国家资源和空间地理基础信息资源的重要组成部分,具有数据复杂、存储格式多样、分布广泛等特点。传统的共享模式对数据类型复杂、异地、异构的数据共享存在困难。而基于元数据的数据共享方法为国土资源部门解决数据共享、信息服务社会化提供了重要途径。以空间元数据为核心,采用XML描述元数据标准和Web服务的架构模式,设计了一个面向国土资源的空间信息资源共享模型。     

面向语义信息共享的元数据模型的研究与实现

元数据在国内依然是一个研究热点,本文面向基于语义的信息资源共享就如何利用人工智能领域内的本体(ontology)理论,建立用于描述信息资源语义及其之间关系的元数据模型进行了研究,并初步实现了基于元数据模型的信息资源元数据描述模版和描述工具原型.     

元数据管理的价值

在Gartner副总裁Carl Claunch看来,元数据管理未来将会是对数据中心产生重大影响的十项技术之一。对于什么是元数据,目前还存在着多种不同的描述方式。最通俗的定义便是对数据资源的描述,英文名称为“Metadata”,通常被解释为“data aboutdata”,即关于数据的数据。元数据是信息共享和交换的基础和前提,用于描述数据集的内容、质量、表示方式、空间参考、管理方式以及数据集的其他特征。元数据管理,则是对技术元数据和业务元数据进行管理,其目标是为了提升共享与重新获取、理解企业信息资产的水平。     

RDF文档解析器及查询语言的实现

RDF是W3C提出的用于描述Web资源的元数据的标准.它使用<subject, predicate, object>这样的三元组结构来描述资源的信息,并用XML来序列化这些三元组.文中的工作包括两个方面一是解析XML形式的RDF文档,将其转换成三元组格式;二是设计并实现了基于三元组格式的元数据的查询语言.     

Formalizing and validating the web quality model for web source quality evaluation

The proposed web quality model (WebQM) is formalized with ISO/IEC Z language and empirically studied based on the Structural Equation Modeling (SEM) approach. By building the sample data set and constructing the structure equation model, the goodness-of-fit of WebQM is analyzed based on generalized least square method. A web source quality evaluation process based on validated WebQM is implemented and verified as more objective and credible, because the weights of quality criteria are automatically produced in the validation procedure, which avoids the subjective weight assignment in some classic assessment approaches. The model validation and implemented evaluation show that WebQM fits the real web source quality data and is feasible, reliable, and effective for web source quality evaluation.     

Distributing decision support systems on the WWW: the verification of a DSS metadata model

The explosion of information on the World Wide Web (WWW) and on corporate Intranets has made it increasingly important to have methods of organizing and understanding the available content. One method being used to facilitate both the location of specific Web content and the assessment of its quality is metadata. This paper focuses on verifying a metadata model designed for distributing decision support systems (DSS) on the Web. The verification utilizes an experiment to assess end-users' understanding of specific DSS.     

Semantic web technologies for video surveillance metadata

Video surveillance systems are growing in size and complexity. Such systems typically consist of integrated modules of different vendors to cope with the increasing demands on network and storage capacity, intelligent video analytics, picture quality, and enhanced visual interfaces. Within a surveillance system, relevant information (like technical details on the video sequences, or analysis results of the monitored environment) is described using metadata standards. However, different modules typically use different standards, resulting in metadata interoperability problems. In this paper, we introduce the application of Semantic Web Technologies to overcome such problems. We present a semantic, layered metadata model and integrate it within a video surveillance system. Besides dealing with the metadata interoperability problem, the advantages of using Semantic Web Technologies and the inherent rule support are shown. A practical use case scenario is presented to illustrate the benefits of our novel approach.     

Metadata Community Profiles for the Semantic Web

Metadata is needed to facilitate data sharing among geospatial information communities. Geographic Metadata Standards are available but tend to be general and complex in nature and also are not well suited to overcome semantic heterogeneities across vocabularies of different domains and user communities. Current formalizations of metadata standards are not flexible enough to allow reuse and extension of metadata specifications, in particular for Web based information systems. In order to address this problem we propose a methodology to create community specific metadata profiles for the Semantic Web by reusing metadata specifications and domain vocabularies encoded as resources for the Web. This ensures that these community profiles are semantically compatible so they can be used in Web based information systems. The ISO-19115:2003 geographic metadata standard is the most general standard available and is being used in conjunction with the Web Ontology Language as the expression medium to test the methodology for each one of the possible extensions documented in ISO-19115:2003. It is shown that it is possible to extend and reuse metadata specifications and vocabularies distributed in the Web using the Web Ontology Language, by utilizing the language's flexibility to create restrictions on inherit properties and to make interferences on web distributed resources. Examples from the area of Hydrology are provided to demonstrate the technical details of the approach.     

Automatic metadata mining from multilingual enterprise content

Personalization is increasingly vital especially for enterprises to be able to reach their customers. The key challenge in supporting personalization is the need for rich metadata, such as metadata about structural relationships, subject/concept relations between documents and cognitive metadata about documents (e.g. difficulty of a document). Manual annotation of large knowledge bases with such rich metadata is not scalable. As well as, automatic mining of cognitive metadata is challenging since it is very difficult to understand underlying intellectual knowledge about document automatically. On the other hand, the Web content is increasing becoming multilingual since growing amount of data generated on the Web is non-English. Current metadata extraction systems are generally based on English content and this requires to be revolutionized in order to adapt to the changing dynamics of the Web. To alleviate these problems, we introduce a novel automatic metadata extraction framework, which is based on a novel fuzzy based method for automatic cognitive metadata generation and uses different document parsing algorithms to extract rich metadata from multilingual enterprise content using the newly developed DocBook, Resource Type and Topic ontologies. Since the metadata generation process is based upon DocBook structured enterprise content, our framework is focused on enterprise documents and content which is loosely based on the DocBook type of formatting. DocBook is a common documentation formatting to formally produce corporate data and it is adopted by many enterprises. The proposed framework is illustrated and evaluated on English, German and French versions of the Symantec Norton 360 knowledge bases. The user study showed that the proposed fuzzy-based method generates reasonably accurate values with an average precision of 89.39% on the metadata values of document difficulty, document interactivity level and document interactivity type. The proposed fuzzy inference system achieves improved results compared to a rule-based reasoner for difficulty metadata extraction (∼11% enhancement). In addition, user perceived metadata quality scores (mean of 5.57 out of 6) found to be high and automated metadata analysis showed that the extracted metadata is high quality and can be suitable for personalized information retrieval.