基于自然语言理解的SPARQL本体查询

为了用户能够方便地获取本体知识,提出了基于自然语言理解的SPARQL本体查询。利用Stanford Parser分析用户的自然语言查询,根据语法构建查询三元组,与关键词的方法相比,有效地减少了组合的个数。结合用户词典,能较准确地把查询三元组的词汇映射到本体实体。分值计算时除了考虑词语的形式相似和语义相似外,还考虑了概念的模糊性,尽量返回具体的概念。利用本体推理获取隐藏在本体中的信息,对查询进行过滤和限制,提高了准确率。用户通过图形交互界面和系统进行交互,选择需要的结果,最后返回树形查询结果,并能看到相关的信息。实验结果表明,该方法达到了预期的效果。     

Software requirements as an application domain for natural language processing

Mapping functional requirements first to specifications and then to code is one of the most challenging tasks in software development. Since requirements are commonly written in natural language, they can be prone to ambiguity, incompleteness and inconsistency. Structured semantic representations allow requirements to be translated to formal models, which can be used to detect problems at an early stage of the development process through validation. Storing and querying such models can also facilitate software reuse. Several approaches constrain the input format of requirements to produce specifications, however they usually require considerable human effort in order to adopt domain-specific heuristics and/or controlled languages. We propose a mechanism that automates the mapping of requirements to formal representations using semantic role labeling. We describe the first publicly available dataset for this task, employ a hierarchical framework that allows requirements concepts to be annotated, and discuss how semantic role labeling can be adapted for parsing software requirements.     

A computational framework for authoring and searching product design specifications

The development of product design specifications (PDS) is an important part of the product development process. Incompleteness, ambiguity, or inconsistency in the PDS can lead to problems during the design process and may require unnecessary design iterations. This generally results in increased design time and cost. Currently, in many organizations, PDS are written using word processors. Since documents written by different authors can be inconsistent in style and word choice, it is difficult to automatically search for specific requirements. Moreover, this approach does not allow the possibility of automated design verification and validation against the design requirements and specifications.In this paper, we present a computational framework and a software tool based on this framework for writing, annotating, and searching computer-interpretable PDS. Our approach allows authors to write requirement statements in natural language to be consistent with the existing authoring practice. However, using mathematical expressions, keywords from predefined taxonomies, and other metadata the author of PDS can then annotate different parts of the requirement statements. This approach provides unambiguous meaning to the information contained in PDS, and helps to eliminate mistakes later in the process when designers must interpret requirements. Our approach also enables users to construct a new PDS document from the results of the search for requirements of similar devices and in similar contexts. This capability speeds up the process of creating PDS and helps authors write more detailed documents by utilizing previous, well written PDS documents. Our approach also enables checking for internal inconsistencies in the requirement statements.     

航电系统软件需求知识本体构建及评价

针对航电(AE)系统软件密集化程度增加及其软件需求工程中存在的二义性和不完备性等问题,构建 AE 系统软件需求知识本体及其知识框架,在此基础上建立 AE 系统泛化本体,将研究领域限定为飞控(FC)系统,构建飞控系统领域本体。对FC系统领域本体进行评价,结果显示,按照最大隶属度原则,该FC系统领域本体的质量等级为中,需要对其开发技术质量和结构显示质量等方面进行改进。     

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.     

Tools for producing formal specifications: a view of current architectures and future directions

During the last decade, one important contribution towards requirements engineering has been the advent of formal specification languages. They offer a well‐defined notation that can improve consistency and avoid ambiguity in specifications. However, the process of obtaining formal specifications that are consistent with the requirements is itself a difficult activity. Hence, various researchers are developing systems that aid the transition from informal to formal specifications. The kind of problems tackled and the contributions made by these proposed systems are very diverse. This paper brings these studies together to provide a vision for future architectures that aim to aid the transition from informal to formal specifications. The new architecture, which is based on the strengths of existing studies, tackles a number of key issues in requirements engineering such as identifying ambiguities, incompleteness, and reusability. The paper concludes with a discussion of the research problems that need to be addressed in order to realise the proposed architecture.     

Framework of knowledge-based systems : Multiple meta-level architecture for representing problems and problem-solving processes

Currently available expert systems have a performance limit because of the lack of capability to describe problems and problem-solving methods. It is closely related with knowledge representation language, but this is not the only concern with this issue. Real world problems and problem-solving methods are not so simple as to be represented always in the same way by the same language. Their representations must be different depending on various factors involved in the problems themselves and the situations these problems are surrounded with. In this paper, the author discusses first the intrinsic nature of problem representation and problem-solving process representation. The requirements for and the conceptual framework of a knowledge-based system that is suited for dealing with various problems then become apparent quite naturally. The author asserts that a multiple meta-level architecture is necessary as well as a knowledge-representation language that can describe complex data structures as the basic framework of knowledge-based systems.     

Embedable problem-solving architectures: a study of integratingOPS5 with UMass GBB

The requirements of a problem-solving architecture that can be tightly embedded within other architectures and coexist with multiple instances of itself and of other problem-solvers are discussed. The additional effort needed to produce an embedable problem-solving architecture is minor compared to the substantial increase in applicability of the architecture. A specific need for embedable problem-solvers arose with the University of Massachusetts Generic Blackboard Framework (UMass GBB). UMass GBB is based on the blackboard paradigm, which naturally integrates heterogeneous problem-solving representations as individual knowledge sources (KSs). This need is met by developing general specifications for embedable problem-solving architectures, and the specifications are used to modify the public-domain version of OPS5 in order to embed it as an integral KS language within UMass GBB. The OPS5 modifications result in an easily integrated GBB KS language (distributed with the UMass GBB system) that has been used in several GBB applications     

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...     

面向系统能力的形式化分析和测试方法

国内软件业界实施系统测试时,大部分采用对系统规格说明描述的功能点进行逐一测试的方法,很少从系统能力的角度进行测试,难以充分说明系统软件产品满足系统能力需求的要求。同时,系统规格说明使用自然语言进行描述,存在语义不准确的现象,直接影响系统测试的质量。针对上述问题,提出了一种面向系统能力的形式化分析和测试方法。通过该方法,测试工程师可得到语义清晰的系统能力需求描述,并实施面向系统能力的系统测试,有效地提高系统测试的充分性和准确性,从而提高系统软件质量。     

基于本体的构件聚类研究

为了消除自然语言对构件文本信息描述的二义性以及增强术语间的语义关系,文中采用领域本体的思想,给出了一个基于人工智能领域本体的软件构件聚类模型和基于该模型的聚类算法。该模型通过分析领域的共同概念,形成领域本体知识库,提供领域内一致认可的术语,用于匹配对构件文本描述所使用的自然语言。给出的算法通过与基于传统空间向量的K—Means算法分析比较,验证了该算法是有效的,实现了对软件构件更合理的聚类,提高了构件检索的效率和准确性。     

国家食品安全标准图谱的构建及关联性分析

国家食品安全标准（NFSS）既是食品生产者的操作规范，也是食品安全监督的执法准绳。然而，NFSS种类繁多，它们涉及内容广泛，且相互引用关系复杂。为了系统地研究NFSS的内容与结构，对NFSS进行了知识抽取与引用关系挖掘。首先，利用知识图谱（KG）技术提取了标准文件的内容与标准文件之间的引用关系，以这些提取出来的内容作为三元组来构建NFSS知识图谱。然后将这个知识图谱与人工构建的基于危害分析关键控制点（HACCP）标准的食品生产过程本体相关联，使食品安全标准与相关的食品生产过程可以建立联系。同时利用Louvain社区发现算法对图谱中的标准引用网络进行分析，发现了在NFSS中引用度较高的标准及其类型。最后，利用gStore的应用程序接口（API）和Django搭建了一个问答系统，实现了基于自然语言的知识检索与推理，可以在指定需求下查询图谱中影响力较高的NFSS。     

计算机在问题解答领域中理解自然语言的一个实例——SSH系统

本文通过讨论SSH算术应用题解答系统介绍计算机理解自然语言的一个实例.主要讨论SSH 的设计思想,包括知识存贮、理解和分类、推导过程、处理技术、解释和SSH系统解题的例子.     

An approach to user knowledge acquisition in product design

As the world increasingly moves towards a knowledge-based economy, user requirements become an important factor for enterprises to drive product collaborative design evolution. To map user requirements to the product model, user requirements are generally extracted into knowledge that can be used for design decisions. However, because users are interest-driven participants and not professional design engineers, the effect of user knowledge acquisition is not ideal. There are significant challenges for rapid knowledge acquisition with dynamic user requirements. This paper presents an approach to user knowledge acquisition in the product design process, which obtains the tangible requirements of users under the premise that users are adequate for participation. In this approach, the typical information flow is divided into four stages: submission, interaction, knowledge discovery, and model evolution. In the submission stage, natural language processing technology is used to transform text form solutions into data, so that computer technology can be applied to manage large-scale user requirements. In the interaction stage, users are helped to improve their solutions by the iterative recommendation process. In the knowledge discovery stage, after less concerned partial solutions are removed and vacant items are predicted to be supplemented, the final collection of user design information is obtained. Finally, based on rough set theory, design knowledge can be extracted to support the decision of the product model. The washing machine design project is used as a case study to explain the implementation of the proposed approach.     

Data summarization ontology-based query processing

Data summarization has recently received considerable attention in the knowledge systems community. This paper discusses the design of data summarization query system. Based on an initial analysis of requirement representations in data summarization, the study develops a generic organization of ontology for data summarization query system. Furthermore, this paper proposes a framework of ontology-based query language of data summarization based on the proposed ontology structure. A prototype project of data summarization ontology-based Query by Examples (QBE) for summarizing the data incompleteness demonstrates the effectiveness of the proposed framework.     

Natural language interface for information management on mobile devices

A natural language interface (NLI) enables the ease-of-use of information systems in performing sophisticated human - computer interaction. To address the challenges of mobile devices to user interaction in information management, we propose an NLI as a promising solution. In this paper, we review state-of-the-art NLI technologies and analyse user requirements for managing notable information on mobile devices. To minimize any technical difficulties arising from developing and improving the usability of NLI systems we develop general principles for NLI design, which fills in a gap in the literature. In order to satisfy user requirements for information management on mobile devices, we innovatively design NLI-enabled information management architecture. It is shown from two usage scenarios that the architecture could lead to reduced effort in user navigation and improved efficiency and effectiveness of managing information on mobile devices. We conclude the article with the implications of this study and suggestions for future direction.     

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。