Case-based analysis in user requirements modelling for knowledge construction

ContextLearning can be regarded as knowledge construction in which prior knowledge and experience serve as basis for the learners to expand their knowledge base. Such a process of knowledge construction has to take place continuously in order to enhance the learners’ competence in a competitive working environment. As the information consumers, the individual users demand personalised information provision which meets their own specific purposes, goals, and expectations.ObjectivesThe current methods in requirements engineering are capable of modelling the common user’s behaviour in the domain of knowledge construction. The users’ requirements can be represented as a case in the defined structure which can be reasoned to enable the requirements analysis. Such analysis needs to be enhanced so that personalised information provision can be tackled and modelled. However, there is a lack of suitable modelling methods to achieve this end. This paper presents a new ontological method for capturing individual user’s requirements and transforming the requirements onto personalised information provision specifications. Hence the right information can be provided to the right user for the right purpose.MethodAn experiment was conducted based on the qualitative method. A medium size of group of users participated to validate the method and its techniques, i.e. articulates, maps, configures, and learning content. The results were used as the feedback for the improvement.ResultThe research work has produced an ontology model with a set of techniques which support the functions for profiling user’s requirements, reasoning requirements patterns, generating workflow from norms, and formulating information provision specifications.ConclusionThe current requirements engineering approaches provide the methodical capability for developing solutions. Our research outcome, i.e. the ontology model with the techniques, can further enhance the RE approaches for modelling the individual user’s needs and discovering the user’s requirements.     

Learning and inferencing in user ontology for personalized Semantic Web search

User modeling is aimed at capturing the users’ interests in a working domain, which forms the basis of providing personalized information services. In this paper, we present an ontology based user model, called user ontology, for providing personalized information service in the Semantic Web. Different from the existing approaches that only use concepts and taxonomic relations for user modeling, the proposed user ontology model utilizes concepts, taxonomic relations, and non-taxonomic relations in a given domain ontology to capture the users’ interests. As a customized view of the domain ontology, a user ontology provides a richer and more precise representation of the user’s interests in the target domain. Specifically, we present a set of statistical methods to learn a user ontology from a given domain ontology and a spreading activation procedure for inferencing in the user ontology. The proposed user ontology model with the spreading activation based inferencing procedure has been incorporated into a semantic search engine, called OntoSearch, to provide personalized document retrieval services. The experimental results, based on the ACM digital library and the Google Directory, support the efficacy of the user ontology approach to providing personalized information services.     

基于领域本体的用户模型的研究*

目前大多数知识管理系统采用基于关键词或关键词向量空间模型表示用户的兴趣偏好。针对该方法不包含语义信息,很难准确表示用户感兴趣的信息,并且难于扩展,提出一种基于领域本体的用户模型。该模型利用用户访问量,采用改进的相似度算法,实现用户分类建立用户模型,体现用户个人偏好。最后将该模型应用于齐齐哈尔货车快速设计系统中,应用表明该模型能准确地反映用户兴趣,且提高了信息检索效率。     

基于模糊UML的装备保障知识建模方法

装备保障业务需求建模是装备保障信息系统研发的重要环节,准确描述业务概念和关系是获取高质量需求分析产品的重要前提。然而,该业务领域中用户目标、业务效果等核心要素常包含模糊或不确定信息,容易引发系统研发各方的需求理解偏差,从而给系统后期的设计、开发带来巨大隐患。针对上述问题,首先从装备保障领域知识建模出发,挖掘本领域核心知识,构成装备保障领域知识本体,在此基础上借助UML建模语言MOF层扩展机制,引入模糊评估属性和建模元素,进而形成一种可用于该领域信息系统业务建模分析的领域特定建模语言。该建模语言对领域内存在的明确和模糊需求信息同样具有良好的表达能力,便于系统研发各方在信息系统需求分析阶段达成共识,进而为准确捕捉装备保障业务需求提供技术支持。     

基于主题图的本体信息检索模型研究

针对本体在定义领域概念时具有规范性、明确性和可共享性等特点,结合主题图对文档资源组织方式具有语义可导航性,提出了一种基于主题图的本体信息检索模型,并给出了模型的形式化定义。选择旅游领域作为研究对象,定义了旅游本体和旅游文档资源主题图,分析了在信息检索模型中利用本体来规范用户自然语言查询输入,识别用户检索意图和扩展查询语义方面的作用,并展示了主题图在语义导航和用户相关度排序方面的价值。最后通过实验表明基于主题图的本体信息检索模型较传统的检索系统有较好的性能。     

基于本体的军事装备知识建模及分析

针对本体建模过程中不同受众具有不同应用需求的问题,结合本体建模七步法和软件开发螺旋模型提出基于需求的螺旋反馈法.首先,明确领域知识范畴和用户需求,进行本体总体设计;其次,领域专家依据本体构建原则评估知识体系;再次,组装知识体系模型,定义本体属性,创建实例,完成本体详细设计;最后,用户评估反馈,进行新一轮的增量迭代,直至...     

Medicine expert system dynamic Bayesian Network and ontology based

The paper proposes an application framework to be used for medicine assisted diagnosis based on ontology and Bayesian Network (DBNO). There are two goals: (1) to separate the domain knowledge from the probabilistic information and (2) to create an intuitive user interface. The framework architecture has three layers: knowledge, uncertainty model and user interface. The contributions of the domain experts are decoupled, the ontology builder will create the domain concepts and relationships focusing on the domain knowledge only. The uncertainty model is Bayesian Network and the probabilities of the variables states are stored in a profile repository. The diagnostician will use the user interface feeded with the domain ontology and one uncertainty profile. The application was tested on a sample medicine model for the diagnose of heart disease.     

A personalized query expansion approach for engineering document retrieval

Engineers create engineering documents with their own terminologies, and want to search existing engineering documents quickly and accurately during a product development process. Keyword-based search methods have been widely used due to their ease of use, but their search accuracy has been often problematic because of the semantic ambiguity of terminologies in engineering documents and queries. The semantic ambiguity can be alleviated by using a domain ontology. Also, if queries are expanded to incorporate the engineer’s personalized information needs, the accuracy of the search result would be improved. Therefore, we propose a framework to search engineering documents with less semantic ambiguity and more focus on each engineer’s personalized information needs. The framework includes four processes: (1) developing a domain ontology, (2) indexing engineering documents, (3) learning user profiles, and (4) performing personalized query expansion and retrieval. A domain ontology is developed based on product structure information and engineering documents. Using the domain ontology, terminologies in documents are disambiguated and indexed. Also, a user profile is generated from the domain ontology. By user profile learning, user’s interests are captured from the relevant documents. During a personalized query expansion process, the learned user profile is used to reflect user’s interests. Simultaneously, user’s searching intent, which is implicitly inferred from the user’s task context, is also considered. To retrieve relevant documents, an expanded query in which both user’s interests and intents are reflected is then matched against the document collection. The experimental results show that the proposed approach can substantially outperform both the keyword-based approach and the existing query expansion method in retrieving engineering documents. Reflecting a user’s information needs precisely has been identified to be the most important factor underlying this notable improvement.     

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。     

SUPPORTING THE CAD STRUCTURAL DESIGN PROCESS WITH KNOWLEDGE-BASED TOOLS

We present in this article an architecture with its correspondent system implementation for the exploitation of semantic aspects in the computer assisted design of Steel Detailing Structures (Structural Design). Our architecture is based in a domain specific standardization effort called CIS/2 that was modeled from a knowledge point of view using an OWL (Ontology Web Language) compliant ontology.

As test case we present a collection of applications based in the proposed schema that were developed within the frame of an R&D project in which an actual structural engineering company participated as test user.     

Transportation ontology definition and application for the content personalization of user interfaces

Ontologies have been largely exploited in many domains and studies. In this paper, we present a new application of a domain ontology for generating personalized user interfaces for transportation interactive systems. The concepts, relationships and axioms of transportation ontology are exploited during the semi-automatic generation of personalized user interfaces. Personalization deals with the capacity of adaptation of a user interface, reflecting what is known about the user and the domain application. It can be performed on the interface container presentation (e.g., layout, colors, sizes) and in the content provided in their input/output (e.g., data, information, document). In this paper, the transportation ontology is used to provide the content personalization. This paper presents the ontology and how it is used for the personalization of user interfaces for developing transportation interactive systems by model-driven engineering.     

基于知识块摘要和词转移距离的高效司法文档分类

随着全国司法机关智能化建设的深入推进,通过信息化建设应用所积累的海量司法文书为开展司法智能服务提供了司法数据分析基础。通过司法文书的相似性分析实现类案推送,可以为司法人员提供智能辅助办案决策支持,从而提高办案的质量和效率。针对面向通用领域的文本分类方法因没有考虑特定司法领域文本的复杂结构和知识语义而导致司法文本分类的效能低问题,提出一种基于司法知识块摘要和词转移距离（WMD）的高效司法文档分类方法。首先为司法文书构建领域本体知识模型,进而基于领域本体,利用信息抽取技术获取司法文档中核心知识块摘要;然后基于司法文本的知识块摘要利用WMD进行司法文档相似度计算;最后利用K最近邻算法进行司法文本分类。以两个典型罪名的案件文档集作为实验数据,与传统的WMD文档相似度计算方法进行对比,实验结果表明,所提方法能明显提高司法文本分类的正确率（分别有5.5和9.9个百分点的提升）,同时也降低了文档分类所需的时间（速度分别提升到原来的52.4和89.1倍）。     

基于本体的个性化协同推荐

推荐系统已成为减轻信息过载时用户负担的关键工具,由于要处理不同形式的用户交互,因此协同推荐要与用户的具体情况和不断变化的兴趣相关。基于此,提出建立上下文相关的协同推荐,以领域本体的形式包含语义知识,把用户配置定义为一个本体。文章描述用户配置本体如何学习、增量更新和如何用于协同推荐。     

基于Ontology的用户模型研究

针对现有本体用户模型的难点与不足，提出了一种改进的基于领域本体的用户模型（OBUM），利用文本挖掘技术构建领域本体，通过本体学习来完成用户模型的学习和更新。     

基于本体的文档知识图形化分析技术研究

网络信息的激增和多样化给有用信息的识别和获取带来了很多困难。本文通过对本体、Web挖掘、知识发现、概念提取、图形化等技术的集成,建立了基于本体的文档知识图形化分析模型,并以仪表领域为例,开发了相应的试验分析工具,使用户能够快速准确地识别所需要的资源,并对所拥有资源的有用性进行准确直观地判断。     

Development of a Software Engineering Ontology for Multisite Software Development

This paper aims to present an ontology model of software engineering to represent its knowledge. The fundamental knowledge relating to software engineering is well described in the textbook entitled Software Engineering by Sommerville that is now in its eighth edition [1] and the white paper, Software Engineering Body of Knowledge (SWEBOK), by the IEEE [2] upon which software engineering ontology is based. This paper gives an analysis of what software engineering ontology is, what it consists of, and what it is used for in the form of usage example scenarios. The usage scenarios presented in this paper highlight the characteristics of the software engineering ontology. The software engineering ontology assists in defining information for the exchange of semantic project information and is used as a communication framework. Its users are software engineers sharing domain knowledge as well as instance knowledge of software engineering.     

一种基于文档内容的语义标注方法

互联网上存在海量数据,如何在大量的信息中查找到有用信息就变成了一个至关重要的问题。语义网为解决这一问题带来了曙光。然而当今网络现状与语义网之间存在巨大差距,即海量非结构化的页面内容难直接转化为语义的知识。提出了一种基于文档内容的语义标注方法,利用本体所表达的语义环境,即本体知识相关词汇及其所处的语义上下文环境在文档中出现频率,实现对文档的语义标注。实验显示方法取得良好的效果,但受本体知识质量和标注文档质量两个因素影响较大。     

Agent-based architecture for context-aware and personalized event recommendation

In order to offer context-aware and personalized information, intelligent processing techniques are necessary. Different initiatives considering many contexts have been proposed, but users preferences need to be learned to offer contextualized and personalized services, products or information. Therefore, this paper proposes an agent-based architecture for context-aware and personalized event recommendation based on ontology and the spreading algorithm. The use of ontology allows to define the domain knowledge model, while the spreading activation algorithm learns user patterns by discovering user interests. The proposed agent-based architecture was validated with the modeling and implementation of eAgora? application, which was illustrated at the pervasive university context.     

一种应急预案本体模型及其应用研究*

目前,应急预案是分布于多个单位的非结构化文档,缺乏统一的建模方法,造成对预案描述的领域知识进行表示和利用存在困难。为解决以上问题,提出一种基于本体的知识建模方法,对应急预案文本进行建模,并实现应急领域知识共享。根据对应急预案文本结构特征进行分析,在重用现有本体模型的基础上提出了各主要要素的本体模型,形成一种应急预案本体模型（emergency plan ontology model,EPOM）。通过利用该方法对某区域防汛应急预案进行本体知识建模,开展应用研究。应用结果表明,该方法能够有效建模应急预案描述的     

基于本体的文档知识图形化分析技术研究

网络信息的激增和多样化给有用信息的识别和获取带来了很多困难。本文通过对本体、Web挖掘、知识发现、概念提取、图形化等技术的集成,建立了基于本体的文档知识图形化分析模型,并以仪表领域为例,开发了相应的试验分析工具,使用户能够快速准确地识别所需要的资源,并对所拥有资源的有用性进行准确直观地判断。