基于本体的林业领域文档特征权重模型

传统文档特征权重模型仅考虑关键词本身,文档内其他相关词汇并没有参与计算,信息检索时无法返回全面和准确的结果。为解决该问题提出了一种基于本体的林业领域文档特征权重模型。该模型计算TF-IDF特征权重;结合林业领域本体,分别获取关键词和林业领域内其他词汇的语义距离、语义重合度和概念的层次差,并计算语义相关度;结合TF-IDF和语义相似度的结果计算特征权重。实验证明该模型可以提高文本检索的查准率和查全率,使检索结果更加满足用户的需求。     

软件文档质量的度量方法研究

软件文档的质量一直是软件开发人员,尤其是软件评测人员关注的问题.目前软件文档的质量存在着较多的问题,但是却没有相应的方法来判断文档的质量好坏程度.基于这种状况,提出了度量软件文档质量的一种方法.提出了使用质量度量模型和综合评判模型来度量软件文档质量.通过这个方法的应用,可以进行比较客观的判断文档的质量,同时得出被度量的软件文档存在不足的方面.长期的应用这种方法,可以对软件文档的编写质量进行循序渐进的改进,从而得到让使用人员满意的软件文档.     

基于聚类分析的图模型文档分类

针对传统向量空间模型中的特征项孤立处理问题,首先通过χ2统计和特征聚类相结合的模式实现特征降维,然后使用图模型来建立词和词之间相互关联信息,最后运用KNN方法进行文档分类测试。该算法提高了稀有词对分类的贡献,强化了关联词的分类效果,并降低了文档向量的维数。实验证明,该算法提高了分类的准确率和召回率。     

基于本体的ebXML／R＆R注册分类模型

将本体引入注册分类信息的描述，使用OWL描述注册分类信息本体，从ebXML／RIM中抽象出专门用于管理注册分类信息的注册分类模型，提出了把注册分类信息本体作为注册分类模型的管理对象的设计思想，构造了基于本体的ebXML／R＆R注册分类模型。对于实现ebXML／R＆R与其它信息资源R＆R分类注册方法与技术的互操作性具有重要的理论与实际意义。     

基于领域本体的文档向量空间模型构建

针对VSM不能揭示隐藏在不同特征词后面的相同概念语义、反映文档中的潜在语义关系、在相似度计算中精度较低的问题,提出一种基于领域本体的文档向量空间模型DOBVSM(domain ontology-based vector spacemodel)。该模型把领域本体中的概念扩展为文档特征词,并通过概念间的语义关系对特征词权重进行调整,最终建立包含语义关系的文档DOBVSM。通过实验分析表明:DOBVSM计算的文档相似度值更加发散,与专家评价值最为接近,能够较好地反映文档之间的相似情况。     

本体化可信完整性度量策略匹配模型

通过对可信网络接入完整性度量的分析,结合本体的思想,建立了一个基于本体的可信网络完整性度量模型。该模型对终端接入可信网络的完整性参数进行本体化建模,确定对象关联规则,通过基于免疫的本体匹配算法实现了完整性度量策略的自适应选择分发。分析结果表明,该算法能够有效地对完整性度量参数进行策略的优化匹配。该模型的提出为可信网络下完整性度量的策略授权分发提供了一个新的研究思路     

基于主题本体的信息采集模型研究

互联网上的海量信息,至今还在快速发展,面向主题的信息检索已成为当前的研究热点之一.在提高信息检索的精度方面,一般认为本体技术是解决方法之一.在对领域本体技术和传统的基于主题的信息采集技术的基础上,设计了-个基于领域本体的信息采集模型,给出了模型的体系结构,提出了一种关键词加权的词性相关性计算方法以及利用领域本体及对应的词典判定主题相关度的算法.通过实验验证了所提出的方法在提高检索的准确率方面具有明显的优势.     

基于军事训练本体的文档向量空间模型构建

为解决军事训练文档间语义相关问题,提出一种基于军事训练本体的向量空间模型构建方法。介绍了基于军事训练本体构建文档索引和基于已建索引构建向量空间模型,其中向量空间模型构建的过程主要包括特征项抽取、权重计算和向量空间模型降维三个步骤。实验结果证明,基于军事训练本体的向量空间模型的文档表示方法可以解决文档间的语义相关问题。     

一种基于有向无环图的本体内聚度度量方法

目前,随着本体的广泛使用和快速发展,本体在结构与语义上变得越来越复杂。如何对本体的质量进行评估成为本体构建和重用的主要问题。在本体构建过程中,对本体进行评估有利于对本体进行重构和优化,以构建高质量的本体。在本体重用过程中,可以帮助用户在候选本体集中选择最优结构的本体。提出一种基于有向无环图(DAG)的本体内聚度度量方法,首先依据有向无环图的结构提出一组本体内聚度度量指标;然后根据已有的度量验证框架对其进行验证,说明度量指标在理论上有效;最后使用经典本体数据集进行实验,说明所提出的本体内聚度度量方法的合理性和有效性,有利于本体的构建和重用。     

Agent-based ontology mapping and integration towards interoperability

Abstract: Interoperability is an important issue in ontology research. In this paper, a novel agent-based framework for managing ontologies in a dynamic environment is developed. The framework has several key characteristics such as flexibility and extensibility that differentiate this research from others. Based on the proposed framework, ontology mapping and integration are investigated. It is believed that inter-ontology processes like ontology mapping with logical semantics are foundations of ontology-based applications. Accordingly, several types of semantic relations are proposed and corresponding mapping mechanisms are developed. Based on mapping results, ontology integration is developed to provide abstract views for participating organizations in the presence of a variety of ontologies. A prototype is built to demonstrate the design and functionalities and is applied to beer ontologies. The prototype shows that the framework is not only flexible but also practical. All agents derived from the framework exhibit their behaviours as expected.     

Semantic interoperability with heterogeneous information systems on the internet through automatic tabular document exchange

Internet is a common information space populated with many entities (e.g., Internet of Things) with different information system types. Each of them has its own context of how to build and process documents (e.g., form documents). This leads to heterogeneous documents in terms of syntax and semantics, which are difficult to make information fusion from one context to another. To resolve this problem, this paper uses semantic interoperability technique which consists of two automatic stages including consistent data understanding and reasonable data usage. To implement semantic interoperability, this paper proposes a novel automatic tabular document exchange (DocEx) framework comprised of a new tabular document model (TabDoc) and a semantic inference scheme to fit the two stages above respectively. In this TabDoc model, a new Tabular Document Language (DocLang) as a communication medium between users and devices is provided, which is not only an information representation language but also a rule language for semantic inference as well. Abstract sub-tree-based semantic relations constructing the logical structure of a tabular document are separated from their presentational structures, clarifying the relationship between semantic groups (e.g., a cell or a block) with the help of a common dictionary CONEX. Besides, this paper proposes a semantic inference algorithm (SIA) executing the inference procedure on received tabular documents created by a Table Designer system which integrates with SIA. Finally, the proposed framework is applied to the processing of flight ticket booking in a realistic e-business scenario. The results show that the proposed method in this paper improves the performance of information fusion among different information systems on the Internet.     

一个基于关联规则的多层文档聚类算法

提出了一种新的基于关联规则的多层文档聚类算法,该算法利用新的文档特征抽取方法构造了文档的主题和关键字特征向量。首先在主题特征向量空间中利用频集快速算法对文档进行初始聚类,然后在基于主题关键字的新的特征向量空间中利用类间距和连接度对初始文档类进行求精,从而得到最终聚类。由于使用了两层聚类方法,使算法的效率和精度都大大提高;使用新的文档特征抽取方法还解决了由于文档关键字过多而导致文档特征向量的维数过高的问题。     

支持ERP模型输出的可配置文档生成器

在建立ERP业务模型之后,需要将其进行文档化输出,以协助ERP系统设计与开发人员理解模型并快速开发系统．分析了ERP模型的文档化需求,提出了一种基于页结构的ERP文档模型,建立文档与ERP模型之间的映射关系,并提出了基于XML的文档描述语言DDL。在此基础上,设计了一种文档生成器,通过标准文档模板配置以满足文档格式与内容的个性化需求,通过将ERP模型数据自动写入标准模板以自动生成DDL文档和最终Word文档。     

Toward a business model reference for interoperability services

The importance of interoperability for businesses is undoubted. After an evolution from electronic data interchange to interoperability in electronic business and enterprise interoperability both the scientific and the practitioners’ community are today discussing the notion of interoperability service utilities. Furthermore, researchers are studying decentralized and distributed interoperability approaches such as peer-to-peer networks, for example. However, a comprehensive investigation of business models for such decentralized approaches to interoperability is still missing. Drawing from recent literature on business modeling on the one hand and interoperability research on the other hand this paper designs a business model reference for interoperability services. The business model reference assumes interoperability information as an economic good and is applied in two case studies and evaluated from multiple perspectives. The paper contributes to the scientific body of knowledge as it proposes a novel design artifact which lays the foundation for a number of future research opportunities.     

基于XML的通用测试文档生成方法研究

针对目前软件测试过程中通用文档自动生成所面临的问题,介绍了一种基于XML的通用测试文档生成方法.分析了软件测试文档的基本种类及文档生成的重要性,论述了将XML技术用于通用文档生成中的优势,给出了一个基于XML的通用测试文档生成模型,并探讨了该模型的关键方案设计.     

Semantic relation based personalized ranking approach for engineering document retrieval

Since engineering design is heavily informational, engineers want to retrieve existing engineering documents accurately during the product development process. However, engineers have difficulties searching for documents because of low retrieval accuracy. One of the reasons for this is the limitation of existing document ranking approaches, in which relationships between terms in documents are not considered to assess the relevance of the retrieved documents. Therefore, we propose a new ranking approach that provides more correct evaluation of document relevance to a given query. Our approach exploits domain ontology to consider relationships among terms in the relevance scoring process. Based on domain ontology, the semantics of a document are represented by a graph (called Document Semantic Network) and, then, proposed relation-based weighting schemes are used to evaluate the graph to calculate the document relevance score. In our ranking approach, user interests and searching intent are also considered in order to provide personalized services. The experimental results show that the proposed approach outperforms existing ranking approaches. A precisely represented semantics of a document as a graph and multiple relation-based weighting schemes are important factors underlying the notable improvement.     

基于双语LDA的跨语言文本相似度计算方法研究

基于双语主题模型思想分析双语文本相似性,提出基于双语LDA跨语言文本相似度计算方法。先利用双语平行语料集训练双语LDA模型,再利用该模型预测新语料集主题分布,将新语料集的双语文档映射到同一个主题向量空间,结合主题分布使用余弦相似度方法计算新语料集双语文档的相似度,使用从类别间和类别内的主题分布离散度的角度改进的主题频率-逆文档频率方法计算特征主题权重。实验表明,改进后的权重计算对于基于双语LDA相似度算法的召回率有较大提高,算法对类别不受限且有较好的可靠性。     

On Capturing Semantics in Ontology Mapping

Semantic interoperability between disparate systems in open, distributed environments has become the quest of many practitioners in a variety of fields. One way to achieve such a goal is through ontology mapping. The perspective users of such technology, however, are faced with a number of challenges including ambiguity of the meaning of mappings, difficulties of capturing semantics, choice of the right ontology mapping tools, verification and validation of results and operationalisation in the beneficiary semantic web application. In this paper we present a formalisation of ontologies and a triangle model for the ontology mapping problems. This formalisation of ontology mapping reflects the engineering steps needed to materialise a versatile mapping system in order to faithfully re-capture the semantics embodied in ontologies which is the fundamental requirements posed by the semantic web environment. We further accommodate this formalisation with a series of specialist algorithms targeting at particular aspects of semantic capturing. Finally, we evaluated the proposed algorithms by way of ontology mapping benchmark tests.