基于Web的群体决策研讨信息自主可视化初探

为了克服在群体决策研讨过程中存在的“信息过载”和“知识断层”以及单纯依赖文本记录方法等给群体交流造成的不便,改善沟通效果并最终有效地辅助决策,需要对研讨信息进行合理组织和表示。文章分析了群体研讨过程中的信息属性及其结构,提出了在研讨某一时点上的信息布局“树状结构”以及在整个研讨进程上的“网络结构”的信息自主可视化概念模型。最后,利用JAVA技术、WEB技术以及多媒体技术等设计并实现了一个简单的体现研讨信息自主可视化思想的平台。     

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。     

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。     

基于主题词的微博热点话题发现

近年来,微博网站已成为海量信息的发布平台。微博丰富的信息为用户提供便利的同时,也带来了信息过载的风险。针对热点话题发现能够降低信息过载的风险,改善用户体验。结合最长公共子串和维基百科知识,提出一种基于主题词的中文微博热点话题发现方法。首先,获取微博数据的高频最长公共子串,作为描述话题的候选主题词;其次,利用维基百科知识,对候选主题词进行筛选;最后,对主题词集合聚类以发现话题,并计算每个话题的能量,从中选取热点话题。在真实数据集上的实验表明,该方法能有效发现微博热点话题。     

基于微博的学生学习资源推荐系统的构建

随着Internet技术的不断发展,信息孤岛、信息过载和资源迷航问题严重影响用户高效率地发现、利用互联网资源。以为学生用户推荐优秀的学习资源为出发点,利用微博技术构建一个为学生用户推荐学习资源的资源推荐平台。该平台以空间向量模型为表示模型,通过Heritrix、SCWS分词器、基于内容且带有协同过滤的混合推荐算法等多种技术来收集、获取、筛选、推介学习资源数据。     

面向在线交易日志的用户购买行为可视化分析

在线交易日志,即用户通过电商平台购买商品产生的交易记录,包括用户、商品、交易及商家的相关信息,反映了用户的购买行为.现有的可视化方法未能充分结合在线交易日志的时序、层次、地理、多维等特征,实现对用户购买行为的多角度分析.对此,本文结合交易日志的多个特征,提出了基于径向布局的复合时序可视化方法和融合空间信息的时间轴可视化方法,设计了颜色极值映射方法和规律映射方法,并基于上述方法,设计并实现了面向在线交易日志的用户购买行为可视化分析系统UPB-VIS,从而完成了单个用户和用户群体购买行为的全方位分析.最后,通过在京东商城在线交易日志数据集上的实验证明了系统的易用性和相关可视化方法的有效性.     

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。     

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。     

集成化可视化的知识检索服务平台建设

本文总结中国科学院用户的主要信息需求,并从数字资源的统一发现、数字资源的关联化和对象化组织、基于知识组织体系的相关性检索技术以及可视化的检索和展示技术方面分析国外相关研究概况,提出集成化可视化知识检索服务平台的体系框架,最后介绍集成化可视化知识检索服务平台的功能实现.     

基于关联规则挖掘的个性化智能推荐服务

1 概述随着WWW上的信息的爆炸性增长,用户的“信息过载”和“资源迷向”问题越来越突出。为了解决用户的信息过载和资源迷向问题,人们发展了许多智能推荐服务系统以及相关技术,帮助用户在WWW上快速定位、检索感兴趣的信息。其中,WebWatcher系统采用跟踪用户浏览Web站点的行为或者访问路径方法,学习用户的访问模式,将用户可能感兴趣的Web页在线推荐给用户。SiteHelper系统采用分析每一个用户已经访问的Web页,学习用户的兴趣模式,从用户感兴趣的Web页(浏览时间超过规定门限或者访问频次超过     

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。     

Argumentation-Based Inference and Decision Making--A Medical Perspective

The argumentation services platform with integrated components (Aspic) project aims to provide advanced argumentation-based computational capabilities. Argumentation is a potentially important paradigm for developing commercial and public services that are flexible and easily understood by human users.     

On-line synchronous scientific argumentation learning: Nurturing students' argumentation ability and conceptual change in science context

The purpose of this study is to examine the difference in effectiveness between two on-line scientific learning programs – one with an argumentation component and one without an argumentation component – on students' scientific argumentation ability and conceptual change. A quasi-experimental design was used in this study. Two classes of 8th grade students (the experimental group) received the on-line scientific argumentation learning program about chemical reaction, and the other two classes of 8th grade students (the control group) received the same on-line scientific learning program about chemical reaction, but without argumentation, for two weeks. All 140 students were administered the scientific conception test, conceptual change test, and argumentation test before, one week after, and eight weeks after learning. In addition, the experimental group students' on-line argumentation process was collected. Results showed that the students of the experimental group significantly outperformed the control group, regardless of scientific conceptions, conceptual change, and argumentation. Regression results indicated that hold of scientific conceptions is the best predicator for students' conceptual change, followed by argumentation ability. The quantity and quality of scientific arguments that students generated in a series of argumentation questions improved across the four topics. In addition, students also successfully changed their conceptions from pre- to post-driving questions across four topics. This clearly demonstrates that students' argumentation ability and conceptual change were both facilitated through receiving the on-line Synchronous Argumentation science learning program.     

Using argument strength for building dialectical bonsai

Argumentation in AI provides an inconsistency-tolerant formalism capable of establishing those pieces of knowledge that can be accepted despite having information in contradiction. Computation of accepted arguments tends to be expensive; in order to alleviate this issue, we propose a heuristics-based pruning technique over argumentation trees. Empirical testing shows that in most cases our approach answers queries much faster than the usual techniques, which prune with no guide. The heuristics is based on a measure of strength assigned to arguments. We show how to compute these strength values by providing the corresponding algorithms, which use dynamic programming techniques to reutilise previously computed trees. In addition to this, we introduce a set of postulates characterising the desired behaviour of any strength formula. We check the given measure of strength against these postulates to show that its behaviour is rational. Although the approach presented here is based on an abstract argumentation framework, the techniques are tightly connected to the dialectical process rather than to the framework itself. Thus, results can be extrapolated to other dialectical-tree-based argumentation formalisms with no additional difficulty.     

An argumentation framework for contested cases of statutory interpretation

This paper proposes an argumentation-based procedure for legal interpretation, by reinterpreting the traditional canons of textual interpretation in terms of argumentation schemes, which are then classified, formalized, and represented through argument visualization and evaluation tools. The problem of statutory interpretation is framed as one of weighing contested interpretations as pro and con arguments. The paper builds an interpretation procedure by formulating a set of argumentation schemes that can be used to comparatively evaluate the types of arguments used in cases of contested statutory interpretation in law. A simplified version of the Carneades Argumentation System is applied in a case analysis showing how the procedure works. A logical model for statutory interpretation is finally presented, covering pro-tanto and all-things-considered interpretive conclusions.     

Data, Information, and Knowledge in Visualization

In visualization, we use the terms data, information and knowledge extensively, often in an interrelated context. In many cases, they indicate different levels of abstraction, understanding, or truthfulness. For example, "visualization is concerned with exploring data and information," "the primary objective in data visualization is to gain insight into an information space," and "information visualization" is for "data mining and knowledge discovery." In other cases, these three terms indicate data types, for instance, as adjectives in noun phrases, such as data visualization, information visualization, and knowledge visualization. These examples suggest that data, information, and knowledge could serve as both the input and output of a visualization process, raising questions about their exact role in visualization.     

Studying the effectiveness of an online argumentation model for improving undergraduate students' argumentation ability

This research develops a web-based model, entitled the “intuitive claim, peer-assessment, discussion, and elaborate claim argumentation training” (IPadE) model, and embeds with a Web-based Interactive Argumentation System to enhance undergraduate students' socioscientific argumentation abilities. This research adopts a quasi-experimental research design; the sample comprised 131 undergraduate students from two classes (69 in the experimental group and 62 in the control group). The socioscientific issue discussed were related to global health. This study collected and analysed quantitative and qualitative data, including the pretest and posttest of students' knowledge test scores and argumentation abilities questionnaire. The results generally confirmed the effectiveness of the IPadE model. First, in a comparison of the content knowledge and argumentation skills, the experimental group have statistically significantly improved than the control group. Second, regarding the number of reasoning modes proposed, the experimental group could propose multiple reasoning modes and reasoning levels on rebuttals increased after training.     

Implementation of Web‐based argumentation in facilitating elementary school students to learn environmental issues

This research develops a Web‐based argumentation system named the Web‐based Interactive Argumentation System (WIAS). WIAS can provide teachers with the scaffolding for argumentation instruction. Students can propose their statements, collect supporting evidence and share and discuss with peers online. This research adopts a quasi‐experimental design, applying WIAS to the teaching of environmental issues, including mudslides, global warming and nuclear power. Fifty‐seven elementary school fifth graders from two classes participated in this research. With each class as a unit, they were divided into the WIAS group (n = 30) and the traditional argumentation instruction (TAI) group (n = 27). Before research, all students took the pre‐test of the ‘achievement test for environmental issues (ATEI)’ and the ‘environmental literacy scale (ELS).’ Then all students received argumentation training and six classes of argumentation instruction. Students in the WIAS group performed argumentation in the WIAS, while those in the TAI group performed argumentation in a traditional classroom. After the six‐class argumentation instruction, all students took the post‐test of the ATEI and ELS. The results show that students in the WIAS group have significantly better learning effectiveness than those in the TAI group. Students in the WIAS group also exhibited significantly better improvement in their environmental literacy.