用户驱动的研讨信息可视化平台的设计与实现

在“以计算机为媒介的群体沟通”环境下,常常出现“知识断层”和“信息过载”。研讨信息可视化丰富了研究和认知手段以及群体发现信息的途径,因而成为缓解“信息过载”的一个重要途径。以研讨用户为中心,从单个信息、信息关系、了解研讨状态、把握研讨过程四个方面识别出研讨用户的信息寻找、发现以及获取的需求;并基于群体研讨支持系统的信息组织模型,设计了用户驱动的研讨信息可视化平台,并结合J2EE、XML、计算机图形学等技术,实现了可视化平台,并结合一个具体应用示范了平台的功能。     

ECBAR系统中群体研讨信息可视化的算法研究*

电子公共大脑视听室为群体研讨提供了动态的可视化信息显示模式,深入研究了其群体研讨信息的自然可视化、自主可视化和智能可视化实现的算法和功能,有助于促进达成共识并有效辅助决策。     

协商研讨环境中的可视化技术研究与实现

利用共识值和关注状态两个协商研讨的重要因素,将隐藏在大量文字中的信息可视化的表现出来,构造了协商研讨环境中基于专家发言的＂研讨树＂,根据研讨信息结构,设计了研讨信息可视化、共识达成趋势可视化和研讨结果可视化的显示模式,实现了基于.net技术的群体协商研讨环境,并通过实验分析了应用效果。     

研讨信息交互式可视化平台设计与实现

针对传统研讨信息静态可视化视图杂乱、难以辨认等问题,提出研讨信息可视化框架和基于交互式可视化技术的解决方案。利用Java、XML技术,借助JFreeChar、Prefuse软件包实现交互式可视化平台。该平台基于节点链接结构,允许用户交互式操作,支持可视化检索和分析。运行结果表明,该平台改善了研讨信息的可访问性,具有较强的可扩展性。     

战争设计工程专家群体研讨模型*

针对战争设计工程中专家群体研讨问题,根据研讨的主题以及目标,将专家群体研讨划分为三类:寻求信息研讨、质询研讨和商议研讨。在研讨类型划分的基础上,建立了战争设计工程群体专家研讨模型。该模型主要用于对战争设计工程中专家群体研讨过程建模,有利于专家对研讨进程的了解。最后阐述了该模型在战争设计工程中的应用。     

一种研讨信息组织模型及其在研讨厅中的应用*

在群体研讨过程中会产生大量的研讨信息,群体共识则蕴藏在这些研讨信息之中,因此有必要对研讨信息进行分析处理。为此,提出一种面向群体共识涌现的研讨信息组织模型(DISM)。该模型根据Toulmin逻辑对专家发言进行结构化处理,将专家发言分解为根据、论证、模态限定和主张等几个部分。其中,模态限定是一个可量化的部件,反映了专家对主张的态度;根据和论证则为主张提供支持。该模型是对研讨信息的全面描述,可以有效处理研讨信息并支持共识达成,最后阐述了该模型在综合集成研讨厅中的应用。     

群体研讨信息智能可视化研究*

重点介绍了智能可视化的各种形式和内容,包括研讨信息统计可视化、关注水平及其状态可视化、共识水平及其状态可视化、共识分析可视化、共识变化预测与建议可视化等,并最终在ECBAR系统中实现了其功能。     

面向综合集成研讨厅的方案生成和评估系统

针对综合集成研讨厅体系,设计并实现了方案生成及评估系统。该系统采用电子问卷的形式供专家撰写和提交方案,自动分析汇总专家群体的方案;并提供了一种评估研讨方案的有效方法,通过专家一致性算法将群体专家的定性评估进行量化,然后实现评估结果的可视化;经过反复研讨评估,得到最终的研讨方案。面向综合集成研讨厅的方案生成和评估系统,采用定性、定量相结合的方法,将与会专家的经验知识和计算机高速的信息处理能力结合起来,为与会专家在综合集成研讨环境中解决复杂问题提供了强有力的工具,实验结果证明了该系统的可行性和可操作性。     

面向战争设计工程的研讨信息组织模型*

提出一种面向战争设计工程的研讨信息组织模型。该模型根据IBIS模型和Toulmin逻辑对专家发言进行结构化处理。根据研讨信息表达的意义,把研讨信息转换为问题节点、方案节点、意见节点和约束条件节点,并根据节点之间的逻辑关系,建立研讨图（DG）。其中,问题节点表示研讨问题和专家对意见和约束条件的质疑;约束条件节点反映专家对意见的判断。该模型是对研讨信息和它们之间逻辑关系的详细描述,最后阐述了该模型在战争设计工程专家群体研讨中的应用。     

基于多Agent的群体协作研讨平台的研究

讨论多Agent技术在群体协作研讨平台中的应用,提出一个简明的基于多Agent的群体研讨协作模型,并在JADE的平台上予以实现.结果表明采用此技术可使专家们在网上的研讨活动更加灵活、便捷和个性化,并使群体共识达成更具科学性.     

A computational model for the identification and assessment of structural similarities in argumentative discourses

Contemporary argumentation systems provide limited or no support for argument and related information processing. This paper presents a generic computational model that is able to identify and assess structural similarities in argumentative discourses. Focusing on the structure of such discourses, we sketch representative scenarios where the proposed model can be applied to a wide range of argumentation systems in order to define, elaborate and mine meaningful argumentation patterns. We argue that the proposed model contributes to both theoretical and practical aspects of argumentation.     

Baseballs and arguments from fairness

This paper applies two argumentation schemes, argument from fairness and argument from lack of knowledge (along with other schemes of lesser prominence) to model the reasoning given by Judge McCarthy supporting his decision to divide the proceeds of a homerun baseball in the case of Popov v. Hayashi. Several versions of both schemes are explained and discussed, and then applied to the argumentation given by Judge McCarthy as the basis of the reasoning used to arrive at his decision. The scheme for argument from fairness is shown to be based on a special principle in Perelman’s theory of justice.     

Computer-supported argumentation: A review of the state of the art

Argumentation is an important skill to learn. It is valuable not only in many professional contexts, such as the law, science, politics, and business, but also in everyday life. However, not many people are good arguers. In response to this, researchers and practitioners over the past 15–20 years have developed software tools both to support and teach argumentation. Some of these tools are used in individual fashion, to present students with the “rules” of argumentation in a particular domain and give them an opportunity to practice, while other tools are used in collaborative fashion, to facilitate communication and argumentation between multiple, and perhaps distant, participants. In this paper, we review the extensive literature on argumentation systems, both individual and collaborative, and both supportive and educational, with an eye toward particular aspects of the past work. More specifically, we review the types of argument representations that have been used, the various types of interaction design and ontologies that have been employed, and the system architecture issues that have been addressed. In addition, we discuss intelligent and automated features that have been imbued in past systems, such as automatically analyzing the quality of arguments and providing intelligent feedback to support and/or tutor argumentation. We also discuss a variety of empirical studies that have been done with argumentation systems, including, among other aspects, studies that have evaluated the effect of argument diagrams (e.g., textual versus graphical), different representations, and adaptive feedback on learning argumentation. Finally, we conclude by summarizing the “lessons learned” from this large and impressive body of work, particularly focusing on lessons for the CSCL research community and its ongoing efforts to develop computer-mediated collaborative argumentation systems.     

TOWARD A COMPUTATIONAL ANALYSIS OF PROBABILISTIC ARGUMENTATION FRAMEWORKS

In this article we analyze probabilistic argumentation frameworks (PAFs), defined as an extension of Dung abstract argumentation frameworks in which each argument n is asserted with a probability p_n. The debate around PAFs has so far centered on their theoretical definition and basic properties. This work contributes to their computational analysis by proposing a first recursive algorithm to compute the probability of acceptance of each argument under grounded and preferred semantics and by studying the behavior of PAFs with respect to reinstatement, cycles, and changes in argument structure. The computational tools proposed may provide strategic information for agents selecting the next step in an open argumentation process and they represent a contribution in the debate about gradualism in abstract argumentation.     

Frame-based argumentation for group decision task generation and identification

One of the most important stages of group decision-making is the generation and identification of decision tasks. In this paper, we define a decision task with five elements: decision makers, decision executors, decision objectives, decision problems and decision constrains. Based on this distinction, we present a conceptual model for generation and identification of group decision tasks in an organization. In addition, we describe a prototype of a group argumentation support system (GASS) that applies frame-based information structure in electronic brainstorming (EBS) and argumentation to support group decision task generation and identification. Using four group performance indicators, the prototype was evaluated in a lab experiment to determine its effectiveness and efficiency.     

基于可信度的辩论模型及争议评价算法

辩论是智能主体间为了消除分歧的一种基于言语的交互行为.由于知识的局限性,争议以及争议内部的陈述通常存在不确定性,因此在对辩论进行建模时需要考虑不确定信息处理问题.提出一种基于可信度的辩论模型（CFA）,该模型将争议表示为由若干前提和一个结论组成的可废止规则,并用对话树描述辩论推演过程.为了表示不确定性推理,引入可信度模型,将争议前提的不确定性和争议之间的攻击强度统一用可信度因子表示.在此基础上,提出计算陈述可信度的争议评价算法,并通过设定可信度阈值确定陈述的可接受性,得出最终辩论结果.最后,用一个实例说明该方法的有效性.该模型可以有效处理不确定信息条件下辩论推理过程,其辩论算法建立在数值计算基础之上,所得出的可接受陈述集在给定可信度阈值条件下是唯一的,可以克服Dung 的抽象辩论框架中扩充语义的不足.     

基于价值辩论框架的决策支持技术研究

在复杂、开放、不确定的环境中,决策者都面临着对行动方案进行论证与选择的难题.基于辩论的决策支持技术是近年来出现的不同于传统辅助决策理论的新方法,它使用论据辅助决策制定和解释决策的理由.首先总结分析了当前基于价值辩论框架的决策支持模型存在的不足与缺陷,提出了论据分类的思想,然后根据该思想设计了ArguDecision辩论...     

A logic of argumentation for specification and verification of abstract argumentation frameworks

In this paper, we propose a logic of argumentation for the specification and verification (LA4SV) of requirements on Dung??s abstract argumentation frameworks. We distinguish three kinds of decision problems for argumentation verification, called extension verification, framework verification, and specification verification respectively. For example, given a political requirement like ??if the argument to increase taxes is accepted, then the argument to increase services must be accepted too,?? we can either verify an extension of acceptable arguments, or all extensions of an argumentation framework, or all extensions of all argumentation frameworks satisfying a framework specification. We introduce the logic of argumentation verification to specify such requirements, and we represent the three verification problems of argumentation as model checking and theorem proving properties of the logic. Moreover, we recast the logic of argumentation verification in a modal framework, in order to express multiple extensions, and properties like transitivity and reflexivity of the attack relation. Finally, we introduce a logic of meta-argumentation where abstract argumentation is used to reason about abstract argumentation itself. We define the logic of meta-argumentation using the fibring methodology in such a way to represent attack relations not only among arguments but also among attacks. We show how to use this logic to verify the requirements of argumentation frameworks where higher-order attacks are allowed [A preliminary version of the logic of argumentation compliance was called the logic of abstract argumentation?(2005).]     

基于IBIS和Toulmin辩论形式的群体研讨模型

研讨模型是建立群体研讨环境的理论基础。以基于问题的信息系统(IBIS)模型和Toulmin辩论模型为基础,建立了一种可对研讨发言进行评价的群体研讨模型。该模型将群体研讨发言信息组织成由发言节点和语义边构成的图。给出了基于语言加权集结(LWA)算子和节点归约的发言节点评价方法。以系统体系结构设计问题的群体研讨为例,说明模型的可用性和有效性。     

论维吾尔语SUBS＋NP结构的形式化描述

该文按照数理逻辑的方法从句法格式,论元及论元模式,动词和名词之间语义关系及逻辑表达式等四个方面对SUBS+NP结构进行初步的形式化描述为自然语言信息处理服务。结果表明维吾尔语SUBS+NP结构中动词与名词之间的多种语义关系决定动词可能选择的表达形式即“”型动名词形式和形动词形式,并且动词与名词之间的语义关系服从句法的编码,借助两种句法形式表现出不同的语义内容。