一种面向主题的web知识检索方法

知识检索研究如何从数据和信息中抽取知识,在数据和信息日益增长的今天,知识检索显得尤为重要。现有的知识检索主要以事先构造好的知识库为基础,需要通过专家来构建和维护用于检索的知识库。然而,人工构建知识库非常耗时而且代价很高,而且,基于事先构造好的知识库的检索结果也被局限于知识库覆盖的范围,不具有动态性和时变性。本文提出了一种基于Web的面向主题的知识检索方法。该方法一方面以开放动态的Web信息为基础,支持动态即时的知识检索;另一方面,以用户选定的主题为中心,从Web信息中动态获取知识,构成与用户主题相关的知识检索结果,不局限于某个特定领城。     

基于工业设计企业的多策略知识检索系统

为了提高工业设计企业的企业知识的检索效率,更好的达到知识共享重用,提出了基于工业设计企业的知识检索系统设计方法.分析了工业设计企业知识特征,针对企业的知识特征建立了基于本体可配置的企业知识库模型,通过本体表达企业知识结构,利用知识实例表达企业具体知识.以此为基础,研究了基于知识属性的知识推理方法,提出了可配置的多策略知识检索方法,在检索过程中利用用户配置信息和用户语境信息,通过知识推理对不同特征知识进行多策略知识检索.     

基于世界知识的深网数据源增强分类模型

针对传统词袋方法在深网(Deep Web)数据源分类应用中的局限性,提出一种基于世界知识的Deep Web数据源增强分类模型,通过对外部知识库的主题分析,建立特征映射,构造基于领域概念的辅助分类器,丰富Deep Web查询表单的特征集合。基于Wikipedia百科知识库对真实Web数据进行分类。实验结果证明该模型有效。     

基于本体的知识库个性化检索方法研究

在使用本体技术构建知识资源检索系统的研发过程中,常会遇到检索结果同检索者本身实际情况不符,以及计算机难以理解用户实际需求的问题。为此,我们提出了一种基于本体的知识库个性化检索方法,将知识服务的本体构建、服务定义的过程同用户的个性化信息有机结合起来,并在服务执行的使用用户个性化信息来优化执行结果。实践表明,该方法可以比较精确的识别用户个性化需求,简化用户输入,提升查询结果质量。     

基于本体的知识库个性化检索方法研究

在使用本体技术构建知识资源检索系统的研发过程中,常会遇到检索结果同检索者本身实际情况不符,以及计算机难以理解用户实际需求的问题。为此,我们提出了一种基于本体的知识库个性化检索方法,将知识服务的本体构建、服务定义的过程同用户的个性化信息有机结合起来,并在服务执行的使用用户个性化信息来优化执行结果。实践表明,该方法可以比较精确的识别用户个性化需求,简化用户输入,提升查询结果质量。     

基于开放网络知识的信息检索与数据挖掘

网络大数据是指"人、机、物"三元世界在网络空间(cyberspace)中交互、融合所产生并在互联网上可获得的大数据.这些数据具有多源异构、交互性、时效性、社会性、突发性和高噪声等特点,不但非结构化数据多,而且数据的实时性强.网络大数据背后蕴含着丰富的、复杂关联的知识.建立面向开放网络的知识库是获取网络大数据中的丰富知识的有效手段.对当前国内外主要的开放网络库进行了比较,分析了相应的构建方法、多源知识的融合以及知识库的更新等关键技术.进一步从用户意图理解、查询扩展、语义问答、线索挖据、关系推理以及关系和属性预测等方面出发,总结了基于开放网络知识库的信息检索、数据挖掘与系统应用的研究现状和主要问题.最后,对开放网络知识库的发展趋势和面临的主要挑战进行了展望.     

面向Deep Web不确定知识表示的动态模糊描述逻辑

Deep Web信息量大,主题专一,信息质量好.然而Deep Web信息存在着不确定问题,因此难以对其进行知识表示和推理.基于动态模糊逻辑理论,提出了一种新的描述逻辑,即动态模糊描述逻辑(DFDLs).给出了DFDLs形式化定义以及DFDLs的语法和语义,设计了DFDLs的tableau的推理算法和策略.采用动态模糊描述逻辑对面向Deep Web的不确定知识进行表示并实现合理的推理和利用,能更好地表达Deep Web的动态和模糊信息.     

一种自适应语义Web检索方法

基于内容的语义Web检索只考虑内容本身,没有考虑用户的不同,不能准确反映用户需求。为此,提出一个自适应语义Web检索框架,对于Web中文文档,借助HowNet知识库给出一种本体学习方法,通过提取用户客观、显式和隐式信息建立用户信息库,并设计用户初始查询本体和个性化查询本体构建算法,从而实现用户的自适应检索。实验结果表明,该方法具有较高的检索效率。     

基于情境面向Web服务的软件安全中间件模型

针对动态、开放的环境,提出了一种基于情境面向Web服务的软件安全中间件模型.该模型通过定义策略规则,使Agent在不中断Web服务运行的情况下,动态调整用户的访问控制.通过对用户及Web服务的情境信息的收集和管理,使得Agent在决策用户的访问控制时,能够动态地适应环境变化.基于该软件安全中间件模型,提出了一种基于规则和本体的策略语言ReiC及其相应的混合推理机制,弥补了单一规则和本体在构建知识库方面能力的不足.     

基于知识图谱的老年教育知识库系统设计与实现

在老年教育建设过程中,将信息技术与老年教育特点相结合,为提高老年教育过程中大量的数据、知识存储和查询效率,设计了一种基于知识图谱的老年教育知识库系统.系统以知识图谱为核心,通过对老年教育不同角色的业务进行分析并设计本体,将多领域和多类型的数据通过本体映射,完成知识图谱构建,将繁杂无序的数据形成具有内在多种关联的知识库,并为学员和教师提供在线的知识管理和知识服务功能.与传统的数据管理方式相比,知识检索和信息获取效率得到有效提高.     

An Adaptation of the Vector-Space Model for Ontology-Based Information Retrieval

Semantic search has been one of the motivations of the semantic Web since it was envisioned. We propose a model for the exploitation of ontology-based knowledge bases to improve search over large document repositories. In our view of information retrieval on the semantic Web, a search engine returns documents rather than, or in addition to, exact values in response to user queries. For this purpose, our approach includes an ontology-based scheme for the semiautomatic annotation of documents and a retrieval system. The retrieval model is based on an adaptation of the classic vector-space model, including an annotation weighting algorithm, and a ranking algorithm. Semantic search is combined with conventional keyword-based retrieval to achieve tolerance to knowledge base incompleteness. Experiments are shown where our approach is tested on corpora of significant scale, showing clear improvements with respect to keyword-based search     

Web 2.0下基于案例的知识管理系统

为实现Web 2.0环境下网络知识的获取和共享,提出一种基于案例的知识管理系统。采用案例推理的方法实现知识管理,根据Web 2.0网络环境的特点,在案例表达阶段,为每个案例设置标签属性,使其能实现开放性分类。在案例检索阶段,将领域本体引入相似度的计算。利用人工神经网络算法、用户录入案例标签维护案例库和本体库。实验结果表明,该系统能快速检索出具有较高相似度的历史案例。     

基于用户访问信息的数据挖掘方法及其算法

旨在探讨一种新的Web访问信息挖掘方法及其算法。分析一般知识发现与Web挖掘方法,提出常见的基于Weblog访问信息的数据挖掘方法存在的局限性,在此基础之上,提出了一种基于自建访问信息收集库的Web访问信息挖掘方法,详细阐述了其中的知识仓库导航页面集与用户访问行为的描述方法,以及访问事务库的挖掘算法。该新方法具有更简便、灵活、高效的特点。     

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.     

基于用户兴趣的查询扩展语义模型

自然语言中词的同义现象和歧义现象一直是降低信息检索查全率和查准率的关键,在Web搜索引擎上显得更加突出。提出了一种基于用户兴趣的查询扩展语义模型,通过构建基于Yahoo的语义ontology知识库消除同义现象,设计客户端的用户兴趣挖掘模型消除歧义现象。实验结果显示该方法能有效提高Web信息检索的查全率与查准率。     

支持Internet上个性化信息重组与发布的Web挖掘关键技术的研究

Internet上个性化信息的重组与发布是Web个性化技术的一个重要组成部分,这一领域目前存在的主要问题是:并非没有信息重组和发布的工具,而是缺乏能够使这类工具高效工作的支持技术。本文提出一种将流数据处理技术引入Web点击流、IP地址流及页面文本流挖掘和分析过程,研究基于Web数据流挖掘的用户行为和需求分析方法;将本体和领域知识引入Web内容挖掘过程,研究领域知识指导下的Web内容挖掘方法;将基于Web数据流挖掘的用户行为和需求分析与领域知识指导下的Web内容挖掘相结合,研究Internet上Web信息模式和Web用户模型及其相互关系的建立;将上述研究成果应用于实际,以期达到高效地支持Internet上满足用户个性化要求的信息重组与发布的目的。     

一种基于领域本体的资源反馈检索模型研究

针对现有资源平台无法互通共享资源,资源库检索系统仅依靠用户输入的单词关键字描述检索资源而无法挖 掘用户需求中的语义信息的问题,提出了一种基于本体的资源反馈检索模型。该模型通过构建本体、概念相似度计算、查询关 键字扩展等关键技术,利用了用户多次反馈中的包含语义知识,满足了用户的查询需求。实验表明,该模型能够有效提高检索 的性能。     

Fuzzy User Modeling for Information Retrieval on the World Wide Web

Information retrieval from the World Wide Web through the use of search engines is known to be unable to capture effectively the information needs of users. The approach taken in this paper is to add intelligence to information retrieval from the World Wide Web, by the modeling of users to improve the interaction between the user and information retrieval systems. In other words, to improve the performance of the user in retrieving information from the information source. To effect such an improvement, it is necessary that any retrieval system should somehow make inferences concerning the information the user might want. The system then can aid the user, for instance by giving suggestions or by adapting any query based on predictions furnished by the model. So, by a combination of user modeling and fuzzy logic a prototype system has been developed (the Fuzzy Modeling Query Assistant (FMQA)) which modifies a user's query based on a fuzzy user model. The FMQA was tested via a user study which clearly indicated that, for the limited domain chosen, the modified queries are better than those that are left unmodified. Received 10 November 1998 / Revised 14 June 2000 / Accepted in revised form 25 September 2000     

基于知识库的开放领域问答系统

问答系统能够理解用户问题,并直接返回答案。现有问答系统大多是面向领域的,仅能回答特定领域的问题。文中提出了基于大规模知识库的开放领域问答系统实现方法。该系统首先采用自定义词典分词和CRF模型相结合的方法识别问句中的主体;其次,采用模糊匹配方法将问句中的主体与知识库中实体建立链接;然后,通过相似度计算以及规则匹配等多种方法识别问句中的谓词并与知识库实体的属性建立关联;最后,进行实体消歧和答案获取。该系统平均F-Measure值为0.695 6,表明所提方法在基于知识库的开放领域问答上具有可行性。     

Integrating web service and semantic dialogue model for user models interoperability on the web

Nowadays there is a great number of Web information systems that build a model of the user and adapt their services according to the needs and preferences maintained by the user model (UM). One of the most challenging issues of this scenario is the possibility to enable different systems to cooperate in order to exchange the available information about a user. Our aim is to create rich (and scalable) communication protocols and infrastructures to enable consumers and providers of UM data to interact. Our solution for dealing with such an issue is to exploit Web standards for interoperability (i.e. Semantic Web and Web Services) for implementing simple atomic communication, and a dialogue model for implementing enhanced communication capabilities. In particular, two systems can start a semantics-enhanced Dialogue Game as a form of negotiation to clarify the meaning of the requested concepts when a shared knowledge model does not exist, and to approximate the response when the exact one is not available. We propose a distributed semantic conversation framework based on the Sesame semantic environment for the exchange of user model knowledge on the Web. Systems have to expose their user model data as a Web Service, and to exploit a public dialogue knowledge base to start the dialogue. The main advantage of the approach is to allow systems to deal with difficult situations by starting an appropriate dialogue game instead of stopping the communication as in the traditional “all-or-nothing” Web Service approach. On the basis of a preliminary evaluation, the approach has shown an improvement of the adaptation results provided by the systems we tested.