基于多粒度语义交互的抽取式多文档摘要

信息爆炸是信息化时代面临的普遍性问题, 为了从海量文本数据中快速提取出有价值的信息, 自动摘要技术成为自然语言处理(natural language processing, NLP)领域中的研究重点. 多文档摘要的目的是从一组具有相同主题的文档中精炼出重要内容, 帮助用户快速获取关键信息. 针对目前多文档摘要中存在的信息不全面、冗余度高的问题, 提出一种基于多粒度语义交互的抽取式摘要方法, 将多粒度语义交互网络与最大边界相关法(maximal marginal relevance, MMR)相结合, 通过不同粒度的语义交互训练句子的表示, 捕获不同粒度的关键信息, 从而保证摘要信息的全面性; 同时结合改进的MMR以保证摘要信息的低冗余度, 通过排序学习为输入的多篇文档中的各个句子打分并完成摘要句的抽取. 在Multi-News数据集上的实验结果表明基于多粒度语义交互的抽取式多文档摘要模型优于LexRank、TextRank等基准模型.     

支持创新型组织学习:基于任务情景的知识适用性管理

面临商务环境的快速变迁和难以预测,创新型组织学习正在成为组织提高生存、适应和竞争能力的关键途径.然而,现有的KM技术对于如何支持创新型组织学习,没有进行深入、系统的研究;导致知识工作者在获取适用性好的信息体(从而促进业务创新)和主动参与OM开放性进化(以促进创新知识的传播和共享)方面缺乏有效的支持.文中提出基于任务情景的知识适用性管理方法KAMTC,旨在以基于应用域本体的任务情景描述模式作为统一的语义基础,去确切、全面和便捷地描述业务工作的查询需求和受检信息体的适用性,以克服这些挑战性问题,进而有效支持知识创新和创新型组织学习的展开.     

基于自注意力网络的时间感知序列化推荐

随着信息技术的发展, 推荐系统作为信息过载时代的重要工具, 正扮演着越来越重要的角色. 基于内容和协同过滤的传统推荐系统, 倾向于以静态方式对用户与商品交互进行建模, 以获取用户过去的长期偏好. 考虑到用户的偏好往往是动态的, 且具有非持续性和行为依赖性, 序列化推荐方法将用户与商品的交互历史建模为有序序列, 能有效捕获商品的依赖关系和用户的短期偏好. 然而多数序列化推荐模型过于强调用户-商品交互的行为顺序, 忽视了交互序列中的时间信息, 即隐式假设了序列中相邻商品具有相同的时间间隔, 在捕捉包含时间动态的用户偏好上具有局限性. 针对以上问题, 文中提出基于自注意力网络的时间感知序列化推荐(self-attention-based network for time-aware sequential recommendation, SNTSR)模型, 该模型将时间信息融入改进的自注意力网络中, 以探索动态时间对下一商品预测的影响. 同时, SNTSR独立计算位置相关性, 以消除可能引入的噪声相关性, 增强捕获用户序列模式的能力. 在两个真实世界数据集上的大量实验表明, SNTSR始终优于一组先进的序列化推荐模型.     

知识图谱增强的神经协同过滤推荐方法

推荐系统已经广泛应用于各领域以处理信息过载问题,但传统方法面临着数据稀疏的挑战,且使用矩阵分解也不能很好的捕获抽象的非线性交互.考虑到知识图谱可以提供丰富的边信息,文中提出一种知识图谱增强的神经协同过滤推荐方法.首先获取项目相关的元数据,将其构建为知识图谱,并利用表示学习方法获取图谱中的语义知识;其次,利用结合注意力的邻域传播机制获取图谱中的结构知识,以此增强项目表示;最后将得到的用户和项目表示送入矩阵分解与神经网络中进行推荐.在公开数据集MovieLens上的实验结果表明,该模型能够有效提升推荐结果的准确性.     

笔式用户界面交互信息模型研究

笔式用户界面是Post-WIMP界面的重要形态,在许多领域得到广泛应用.笔式界面设计需要设计者和用户的共同参与.捕获用户使用意图是设计笔式用户界面的前提,连接交互信息的表示与控制则是成功构造界面的关键.依据笔式交互信息连续性及模糊性特征,从设计参与者与交互信息管理两个维度建立了笔式用户界面交互信息模型OICM(orthogonal interaction information architecture coordinate model).从问题知识域、交互任务、规则集合以及上下文关联4个不同的象限对模型进行了详细的描述,并给出了基于XML的实现方法.在对模型进行分析后,介绍了基于OICM模型的开发平台和应用系统实例.     

基于多智能体系统的面向对象本体研究

智能体间的信息交互和行为协调是共同完成被委托任务的必要条件,论文提出了在多智能体系统中智能体本身必须建立领域模型的技术要求,即用本体支持运行时的语义交互。为此,文中用面向对象的知识表示方法描述并建立本体,并以此为基础形成领域操作代数系统和智能体服务描述语言。结合开放购买的仿真案例,表明在一个完整的情景语义交互中,服务提供方需要以智能体服务描述语言表述自己提供服务的方法和过程,而接受服务方必须在理解智能体服务描述语言的基础上,获取某一具体服务。     

城市规划中基于IS的多通道分层整合方法

提出一种基于交互语义的多通道分层整合方法,该方法结合概率以及时间约束等内容,从多通道的输入信息中捕获用户交互意图,形成交互任务。将其应用于虚拟环境中,根据实际需求设计并实现多种多通道交互技术,同时举例分析其整合过程。仿真实验结果表明,该方法是有效可行的。     

利用共用本体构造本体映射

一些代理机语言使得代理机能够理解代理机之间传递的信息的内容和潜在含义.交互中用到的信息载体是本体,由于本体是多种多样的,而且不同的本体对于同一个事物的描述是不一样的,这就阻碍了代理机之间的交互,这个问题被称作交互问题.文中提出共用本体的概念,建立通用的本体体系,首先建立本体与通用本体之间的映射,然后构建两个或两个以上异构本体之间的映射.实验表明,此方法不仅能够解决结构异构问题,也能解决语义异构问题.     

RGPS制导的按需服务组织与推荐方法

随着互联网上各种Web服务数量的快速增长,如何发现满足用户个性化、多样化需求的服务成为亟待解决的关键问题之一.文中提出了一种面向领域问题的、基于角色-目标-流程-服务模型的按需服务组织与推荐方法.该方法在对与领域问题相关的用户角色(R)、目标(G)、流程(P)和服务(S)进行建模的基础上,利用RGPS元素间的关联关系对领域中服务实现了按需组织,同时根据不同的用户需求表达方式相应地设计了3种服务推荐算法.最后,通过实验验证了所提方法的有效性,并结合实际案例介绍了所开发的系统平台.     

混合数字加密技术在安全ONS方案中的应用

ONS服务对整个物联网来说,它是实现全球产品信息定位和跨企业间信息流转的中心枢纽.本人通过全球物联网的权威研究组织 EPCGlobal 颁发的一系列规范的深入研究和对物联网中企业信息交互需求的充分理解.得出研究此领域的关键技术有EPCIS事件的捕获监听及处理,事件的查询订阅,事件查询的回调操作,ONS定位查找,其中核心的问题是EPCIS服务器端的实现以及如何保证ONS查询过程中的安全可信.     

THE QSM ALGORITHM AND ITS APPLICATION TO SOFTWARE BEHAVIOR MODEL INDUCTION

This article presents a novel application of grammatical inference techniques to the synthesis of behavior models of software systems. This synthesis is used for the elicitation of software requirements. This problem is formulated as a deterministic finite-state automaton induction problem from positive and negative scenarios provided by an end user of the software-to-be. A query-driven state merging (QSM) algorithm is proposed. It extends the Regular Positive and Negative Inference (RPNI) and blue-fringe algorithms by allowing membership queries to be submitted to the end user. State merging operations can be further constrained by some prior domain knowledge formulated as fluents, goals, domain properties, and models of external software components. The incorporation of domain knowledge both reduces the number of queries and guarantees that the induced model is consistent with such knowledge. The proposed techniques are implemented in the ISIS tool and practical evaluations on standard requirements engineering test cases and synthetic data illustrate the interest of this approach.     

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.     

Enhancing problem frames with scenarios and histories in UML-based software development

Abstract: Problem frames are an approach to requirements modelling that is gaining increasing attention and popularity, as it addresses the essential activity of understanding and describing the problem to be solved before undertaking the actual development phases. This paper reports a study concerning the possibility of enhancing the problem frames methodology with concepts derived from requirements modelling techniques based on scenarios and histories. The goal of this research is to make problem frames even more appealing to software developers, who are generally familiar with the ideas underlying scenario-based modelling. The results presented here are encouraging: a well-known problem, often used to illustrate problem frames (the sluice gate control), was studied with the help of scenarios, modelled by means of histories. Scenarios were also employed to support the merging of subproblems, for addressing the frame concern issues and for supporting design models. In all these activities the proposed approach proved helpful.     

Deriving problem frames from business process and object analysis models

While Problem Frames have become a useful approach for requirements analysis, little research has been made to explore how to derive them from a complex problem context. The purpose of this paper is to propose such an approach. The proposed approach consists of three steps to drive the development of Problem Frames. In the first step, business process models are developed to capture the behavioural view of the problem context. In the second step, object analysis models are used to capture the structural view of the problem context. Together, these two views collectively and adequately capture the early context knowledge. These two types of model will then be used in the third step to construct context diagrams and derive Problem Frames. A complex real‐world problem – equity trading problem – is used to illustrate this approach.     

支持MDA的交互式需求获取方法及辅助工具

为支持MDA的开发模式,本文提出了表格驱动的交互式需求获取方法并开发了相应的支持工具.该方法通过填写参与者表、非功能性需求表、用例卡、CRC卡以及用户反馈表来得到用户需求,为建立计算独立模型CIM和平台独立模型PIM提供足够的信息.     

The state of the art in automated requirements elicitation

ContextIn large software development projects a huge number of unstructured text documents from various stakeholders becomes available and needs to be analyzed and transformed into structured requirements. This elicitation process is known to be time-consuming and error-prone when performed manually by a requirements engineer. Consequently, substantial research has been done to automate the process through a plethora of tools and technologies.ObjectiveThis paper aims to capture the current state of automated requirements elicitation and derive future research directions by identifying gaps in the existing body of knowledge and through relating existing works to each other. More specifically, we are investigating the following research question: What is the state of the art in research covering tool support for automated requirements elicitation from natural language documents?MethodA systematic review of the literature in automated requirements elicitation is performed. Identified works are categorized using an analysis framework comprising tool categories, technological concepts and evaluation approaches. Furthermore, the identified papers are related to each other through citation analysis to trace the development of the research field.ResultsWe identified, categorized and related 36 relevant publications. Summarizing the observations we made, we propose future research to (1) investigate alternative elicitation paradigms going beyond a pure automation approach (2) compare the effects of different types of knowledge on elicitation results (3) apply comparative evaluation methods and multi-dimensional evaluation measures and (4) strive for a closer integration of research activities across the sub-fields of automatic requirements elicitation.ConclusionThrough the results of our paper, we intend to contribute to the Requirements Engineering body of knowledge by (1) conceptualizing an analysis framework for works in the area of automated requirements elicitation, going beyond former classifications (2) providing an extensive overview and categorization of existing works in this area (3) formulating concise directions for future research.     

User and design requirements and production of evidence: using incident analysis data to (1) inform user scenarios and bow ties,and (2) generate user and design requirements

This paper reports on an innovative human–machine interaction methodology adopted to assess the case, role and requirements for a new ground collision awareness technology. Specifically, this paper reports on the analysis of ground collision incident data and the subsequent advancement of user scenarios and bow-ties based on this data analysis, for the purpose of generating preliminary user and design requirements for this technology. In so doing, the requirements elicitation and validation methods used in this research are framed from an epistemological perspective. Accordingly, the particular methods adopted are presented and discussed in terms of concepts of evidence, bearing witness and the distinction between facts and values. As such, this paper promotes thinking about evidence-based design practices. Overall, this evidence-based approach aims to improve the development of scenarios and associated problem solving around technology cases, user requirements and user interface design features. The proposed method is useful in terms of bridging the gap from data analysis to design, and validating design decisions. In this regard, it is argued that the generation of user scenarios based on the analysis of incident data (i.e. data coding and statistical analysis), and the reframing of such scenarios in terms of bow-ties for the purpose of requirements/design envisionment, extends existing scenario-based design approaches. Although the use of bow-ties is not new, the advancement of bow-ties from data-driven scenarios is. Specifically, the bow-tie method was applied in a design context, to support problem solving around design decisions, as opposed to formal risk analysis.     

基于本体的需求自动获取

以企业信息系统为研究背景 ,提出了一种基于本体的需求获取方法 ,该方法用企业本体和领域本体为基本线索 ,引导领域用户全面描述现实系统 ,并通过重用领域需求模型 ,构造应用软件需求模型 .这种方法的主要特点是 :用领域用户可以理解的语言与他们交互 ,让他们能积极地参与需求获取活动 ;需求获取在模型的制导下完成 ,利于保证需求获取的完整性和一致性 ;在多种知识的支持下 ,自动完成对现实系统的理解和目标系统需求模型的构造 .该文将以该方法的总体结构为主线 ,分企业本体和领域本体的结构以及目标系统需求模型的构造两大部分 ,阐述这种方法 .     

Guiding goal modeling using scenarios

Even though goal modeling is an effective approach to requirements engineering, it is known to present a number of difficulties in practice. The paper discusses these difficulties and proposes to couple goal modeling and scenario authoring to overcome them. Whereas existing techniques use scenarios to concretize goals, we use them to discover goals. Our proposal is to define enactable rules which form the basis of a software environment called L'Ecritoire to guide the requirements elicitation process through interleaved goal modeling and scenario authoring. The focus of the paper is on the discovery of goals from scenarios. The discovery process is centered around the notion of a requirement chunk (RC) which is a pair 〈Goal, Scenario〉. The paper presents the notion of RC, the rules to support the discovery of RCs and illustrates the application of the approach within L'Ecritoire using the ATM example. It also evaluates the potential practical benefits expected from the use of the approach