面向领域知识复用的C4ISR系统需求建模方法

为了准确地获取和复用C4ISR系统需求,提出基于多本体的需求获取与建模框架。详细介绍了在此框架下进行需求建模的过程,首先明确用户的目标模型,然后使用目标对已有的领域知识库进行查询,如果发现匹配的目标,则利用目标-任务的映射关系抽取相关知识,如果没有匹配的目标,则生成概念描述框架引导用户提出需求,最后将两部分需求合并形成最终的需求模型。需求建模过程一方面能够复用已有需求,另一方面能够在本体的引导下提出新的需求,保证了需求模型的质量和建模的效率。     

基于语义的决策模型能力评估与选择方法

本体决策模型选择的最佳手段是使计算机在理解决策问题和决策模型自身能力的基础上进行.通过领域本体,决策问题和决策模型可以具备被计算机自动理解的形式化语义.在理解决策问题语义的基础上,系统可选择对应的求解模型类别并获取决策问题内在需求,进而根据对应的候选模型语义对其具备的能力进行评估,选择最适合于决策问题的决策模型.最后,实例分析结果表明了这种模型选择方法是有效且可行的.     

基于用例的领域业务服务本体建模

业务服务本体的作用是规范化描述领域业务活动及其之间关系,形成领域业务的基本知识体系。如何让涉众参与本体的设计,是目前联合本体工程研究的热点问题。通过将概念建模时常用的用例图与迭代式本体构建方法相结合,一方面使用领域本体建立规范的业务模型,另一方面基于用例,从用户视角优化本体模型。该建模方法有助于对领域业务的全面理解,所得到的本体模型可满足不同涉众需求。     

基于本体的陶瓷产品配置模型的获取

有效地获取陶瓷产品配置模型是陶瓷企业实施现大规模定制生产模式的前提。本文首先建立了用户需求本体和陶瓷产品配置本体,并实现了两本体之间的映射,在此基础上完成了用户需求知识向产品配置知识的转换,实现了陶瓷产品配置模型的自动获取。     

一种基于领域本体的用户建模方法

针对当前大多数个性化服务系统的不足,以旅游领域为背景,提出了一种新的基于本体的用户模型构建方法,利用领域本体中的概念、实例和属性描述用户兴趣特征,实现了在语义层次上理解用户兴趣。实验表明,该方法能有效提高用户模型的质量。     

基于用户本体模型的文本信息过滤方法研究

随着互联网信息的快速剧增,文本过滤技术成为互联网内容处理的关键技术,对海量信息处理具有很重要的意义.目前研究热点是基于语义的过滤方法,但是这些方法一般都需要大量规则和领域知识的支持,可用性不是很好.为了使机器更好地理解用户需求和文本内容,使过滤结果更能反映用户的真正需求,提高文本过滤的准确率和召回率,提出了基于用户本体模型UOM的文本信息过滤方法.该方法主要包括UOM构建、文本结构分析、文本概念提取和语义相关度计算等.基于UOM(User Ontology Model)的过滤方法,不仅可以表示复杂的用户需求,而且还避免了领域本体的构建,因而其有效性和实用性得到了很大的提高.通过在网络教学资源的智能按需服务系统中的实际运用,表明此方法能更有效地为用户提供过滤服务.     

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,直至形成正确可用的知识体系。与七步法相比,所提方法强调本体测试和用户需求,以小的分段来构建领域知识模型。此外,运用该方法实现的军事装备知识体系面向作战需求,为军事作战提供强有力的理论支撑。     

AML:一种面向需求的多Agent建模语言

定义一种多Agent系统建模语言AML.该语言基于议会制的多Agent协同构架,融合多种先进方法,采用目标分解的方式从需求获取、系统分析到最后的系统设计,共涉及8种模型:用例模型、目标模型、组织模型、角色模型(任务模型)、交互模型、本体模型、Agent类模型(包括Agent结构模型)、系统配置模型.该语言还给出构造不同模型的工作流,以及不同模型之间相互关联的方式.为了和UML保持一致,AML采用与UML一致的符号系统,对于需要扩展的部分,制定专门的符号来表示.为了验证AML的可行性,在开发一个AML的支撑环境AML-Tools的同时,使用该语言描述一个实例--智能仓库系统的设计和实现.     

基于领域本体与上下文感知计算的智能图书

随着信息化时代的发展, Web已成为各类网络信息的主要平台。但是,呈指数增长的海量信息使有价值知识淹没在信息海洋里,用户对专业领域知识的查找、访问、学习以及维护变得越来越困难。针对这种情况,提出了基于领域本体与上下文感知计算的智能图书系统模型,并以颜色科学为例,根据领域知识特性和共享需求构建颜色科学领域本体,然后通过上下文系统获取实现用户需求的相关上下文信息,在上下文感知计算推理模型中为用户提供特定服务,实现了智能图书系统的相关流程。     

基于本体的领域自动问答系统研究

由于传统信息检索返回的结果难以充分理解用户的问题语义,因此以医学领域本体为例,提出一种具有语义推理的自动问答系统。系统在领域知识本体上,通过链式索引结构抽取问题对应在领域知识本体中的命名实体。为理解问题的语义层次,通过改进CFN汉语框架网结构,给出从领域知识本体直接生成能理解问题语义的QFN问题框架本体的映射算法。运用QFN将自然语言问题转化成RDF三元组结构,自动生成问题对应的SPARQL查询语句,同时调用Jena推理机完成语义推理查询在知识本体中查找并给出问题的相关回答。实验结果表明,该方法相比传统的信息检索,可以理解问题表达语义并给出与问题语义相关度高的答案。     

Automatically multi-paradigm requirements modeling and analyzing: An ontology-based approach

Requirements engineering (RE) is one of the crucial phases in software engineering (cf. ref. [1]). In the 1995 survey[1], 8000 projects undertaken in the whole country have been examined. The result indicated that one third of the projects were never completed and one half of the rest succeeded only partially. Poor requirements have been identified as the source of such failure (45%), in which the lack of user involvement (13%) and requirements incompleteness (12%) are the two major causes. R…     

Towards an Ontological Approach to Information System Security and Safety Requirement Modeling and Reuse

ABSTRACT

Misuse cases are currently used to identify safety and security threats and subsequently capture safety and security requirements. There is limited consensus to the precise meaning of the basic terminology used for use/misuse case concepts. This paper delves into the use of ontology for the formal representation of the use-misuse case domain knowledge for eliciting safety and security requirements. We classify misuse cases into different category to reflect different type of misusers. This will allow participants during the requirement engineering stage to have a common understanding of the problem domain. We enhanced the misuse case domain to include abusive misuse case and vulnerable use case in order to boost the elicitation of safety requirements. The proposed ontological approach will allow developer to share and reuse the knowledge represented in the ontology thereby avoiding ambiguity and inconsistency in capturing safety and security requirements. OWL protégé 3.3.1 editor was used for the ontology coding. An illustration of the use of the ontology is given with examples from the health care information system.     

Elicitation synergy of extracting conceptual tags and hierarchies in textual document

This study develops an ontology building process for extracting conceptual tags and hierarchies in textual corpus. Though humans have been creating ontologies for many years, efficient ontology building processes in textual corpus are extremely ad hoc. Several issues have identified including how to recognize terminology in textual document, name concept tags in terminologies, and derive conceptual hierarchies among concepts. The proposed approach is extraction technique combinations to produce ontology prototype for editors. The empirical feedback indicates that elicitation synergy is productive during the early stages of building. Additionally, this elicitation synergy is especially useful for ontology editors who lack reference models of a working domain and who encounter textual corpus as major knowledge sources.     

基于SWRL的软件需求一致性验证方法

需求质量已经成为确保软件项目成功的一个重要因素,对复杂软件系统的需求进行检查和验证,是需求工程中非常重要的工作。在基于领域本体的需求获取和分析等相关工作基础上,提出了一种基于本体和语义规则的需求一致性验证方法,将自然语言描述的需求分解成若干结构良好的最小需求项,使用领域本体的概念模型对其进行形式化和结构化的表示。通过领域本体中的知识来映射需求语义,采用语义万维网规则语言（SWRL）来定义需求一致性验证的推理规则,并通过实例对此方法进行了分析和验证。     

Towards a Machine of a Process (MOP) ontology to facilitate e-commerce of industrial machinery

Adapting to user's requirements is a key factor for enterprise success. Despite the existence of several approaches that point in this direction, simplifying integration and interoperability among users, suppliers and the enterprise during product lifecycle, is still an open issue. Ontologies have been used in some manufacturing applications and they promise to be a valid approach to model manufacturing resources of enterprises (e.g. machinery and raw material). Nevertheless, in this domain, most of the ontologies have been developed following methodologies based on development from scratch, thus ontologies previously developed have been discarded. Such ontological methodologies tend to hold the interoperability issues in some level. In this paper, a method that integrates ontology reuse with ontology validation and learning is presented. An upper (top-level) ontology for manufacturing was used as a reference to evaluate and to improve specific domain ontology. The evaluation procedure was based on the systemic methodology for ontology learning (SMOL). As a result of the application of SMOL, an ontology entitled Machine of a Process (MOP) was developed. The terminology included in MOP was validated by means of a text mining procedure called Term Frequency–Inverse Document Frequency (TF–IDF) which was carried out on documents from the domain in this study. Competency questions were performed on preexisting domain ontologies and MOP, proving that this new ontology has a performance better than the domain ontologies used as seed.     

Non-functional requirements analysis: deficiencies in structured methods

This paper examines some deficiencies in structured systems development methods that have the effect of overlooking non-functional requirements. Evidence from four case studies shows that non-functional requirements are often overlooked, questioning users is insufficient, methodologies do not help in the elicitation of non-functional requirements and there is a lack of consensus about the meaning and utility of non-functional requirements. Some lessons are drawn from the domain of real time systems development. Finally a framework is advanced for taking a stakeholder approach to the conflict and organisational change issues associated with the elicitation stage of requirements analysis.     

个性化领域知识支持的用户主导需求获取方法

应用软件的需求获取与应用领域的特征密切相关,用户的参与日益受到重视,然而用户对系统的认识通常模糊且不完整,且对于多用户系统,需要拥有局部需求的多用户进行协同,才能得到完整、一致的需求.提出一种用户主导的需求获取方法,根据用户特征及其上下文环境,为用户进行需求定义提供个性化的领域知识支持,包括领域需求资产推荐和对多用户协同需求获取的建议.应用实例说明了该方法的可行性,且对于提高用户参与程度、改进领域知识重用效果,从而最终提高需求获取的质量具有积极意义.     

Identification of ontologies to support information systems development

Ontologies can provide many benefits during information systems development. They can provide domain knowledge to requirement engineers, are reusable software components for web applications or intelligent agent developers, and can facilitate semi-automatic model verification and validation. They also assist in software extensibility, interoperability and reuse. All these benefits critically depend on the provision of a suitable ontology (ies). This paper introduces a semantically-based three stage-approach to assist developers in checking the consistency of the requirements models and choose the most suitable and relevant ontology (ies) for their development project from a given repository. The early requirements models, documented using the i^⁎ language, are converted to a retrieval ontology. The consistency of this retrieval ontology is then checked before being used to identify a set of reusable ontologies that are relevant for the development project. The paper also provides an initial validation of each of the stages.     

Configuring use case models in product families

In many domains such as automotive and avionics, the size and complexity of software systems is quickly increasing. At the same time, many stakeholders tend to be involved in the development of such systems, which typically must also be configured for multiple customers with varying needs. Product Line Engineering (PLE) is therefore an inevitable practice for such systems. Furthermore, because in many areas requirements must be explicit and traceability to them is required by standards, use cases and domain models are common practice for requirements elicitation and analysis. In this paper, based on the above observations, we aim at supporting PLE in the context of use case-centric development. Therefore, we propose, apply, and assess a use case-driven configuration approach which interactively receives configuration decisions from the analysts to generate product-specific (PS) use case and domain models. Our approach provides the following: (1) a use case-centric product line modeling method (PUM), (2) automated, interactive configuration support based on PUM, and (3) an automatic generation of PS use case and domain models from Product Line (PL) models and configuration decisions. The approach is supported by a tool relying on Natural Language Processing (NLP) and integrated with an industrial requirements management tool, i.e., IBM DOORS. We successfully applied and evaluated our approach to an industrial case study in the automotive domain, thus showing evidence that the approach is practical and beneficial to capture variability at the appropriate level of granularity and to configure PS use case and domain models in industrial settings.