用于群体研讨支持系统的主持人支持系统研究
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摘要
群体支持系统(Group Support Systems, GSS)通过在群体任务、主意生成以及群体沟通方面提供多种工具辅助以提高群体工作的效率和效果。GSS可以提高群体工作的效率,减少项目时间。先前研究表明:GSS平均可以减少50%的成本以及90%的项目时间。尽管GSS有提高群体绩效很大的潜力,但是GSS在组织中并没有得到广泛的应用。经验和理论均表明仅仅提供技术并不能带来群体的效率和效果。主持人及协助技术已经成为技术支持的群体协作成功的一个关键因素,可能已经成为GSS广泛应用的瓶颈,尤其是GSS大量的应用于分布式群体这一媒体丰富度低的环境下。故寻求有效的协助策略与支持技术变得更加紧迫,具体表现在以下几个方面:①群体协助已经成为GSS广泛应用的瓶颈因素;②GSS大量的应用于分布式群体环境;③群体协助是一项复杂的社会-技术(Social-Technology)任务。协助(Facilitation)是一项复杂的任务,不仅需要有社会动力学(Social Dynamics)方面的经验,对群体活动的基本原理有很深的认识,还需要有GSS技术方面的知识。
协助是一个动态过程,包括管理人、任务和技术之间的关系,组织任务,以及促成会议有效达成目标等方面的辅助工作。设计有效的协助支持技术,通过合适的技术手段降低主持人的协助负担是一个有效的途径。本文正是基于这样一个思路,通过IT技术降低主持人的认知负担并提高协助效率,提供了一个如何识别群体的研讨状态并做出反应的框架,开发了多项工具,并设计实验证明了这些工具的效果。
本论文的主要工作包括以下几个方面:
1.提出了一个面向解决复杂任务的群体支持系统的概念框架。该概念框架从两个级别管理决策任务:决策任务的管理和群体任务的管理;根据认知过程和各个任务需要的知识及技术,将决策过程分为六个阶段:生成议案、任务识别、任务认知与分解、生成方案、方案选择与进度安排、方案执行与反馈。同时,我们设计了多个工具来支持群体协作。对于决策任务的每个阶段,选择不同的工具集合来支持不同的群体任务。该框架可以降低任务复杂性,辅助任务的分配和人员安排。
2.基于GASS的概念框架,给出了主持人支持系统的系统结构。并基于解决复杂问题的Cynefin框架,从群体交互信息和研讨文本两个角度,识别出了共识水平与状态、关注水平与状态、群体贡献率、群体参与水平四个指标,设计并实现了文本聚类和摘要技术,形成了“感知—理解—响应”的概念结构,辅助主持人设计干涉技术,并选择适当的协助工具。
3.通过分析开放持续公共决策环境下对权重的新的需求及现有权重确定方法的不足,提出了一种群体成员权重确定方法:根据背景信息得到的职能权重和专业权重,作为群体成员的基础权重,并周期性的根据群体的参与意愿、主题把握能力以及发言质量计算研讨绩效权重,作为基础权重的修正。实验表明通过该模型可以达到80%的准确性,即能够作为研讨用户信息质量的一个有效测度。
4.在界定研讨信息属性、定义信息结构及其关系的基础上,按照语义关系,提出共识点、分歧点和争议点的概念,结合共识水平及共识状态、关注水平及关注状态、共识水平变化趋势、关注水平变化趋势四个指标,建立智能可视化模型,并用Java和XML技术设计并实现了基于Web的共识评价、预测及分析智能可视化。以一个实例给出了以人-机结合的系统思想为指导的共识评价和预测方法以及通过共识分析,形成群体注意力聚焦的示范应用。最后用实验的方法分析了智能可视化的应用效果。
5.识别了GASS环境下自动化主题聚类的一些挑战,在简要综述相关技术的基础上,结合GASS的研讨模式、研讨文本特征及中文文本分析的要求,给出了中文分词、停词表处理以及有效词语识别的文本分析技术。提出基于主题分析的特征向量选择方法,并基于自组织映射的神经网络(Self-Organization Map,SOM)思想,用Java语言设计并开发了一个自动聚类工具。实验表明,该工具可以达到0.28的聚类准确率,0.35的聚类全面率,产生0.83的聚类错误率。最后讨论了实验结果,并给出了进一步的研究方向。
The physical dispersion of current organizations, escalating complexity of problems and poor productivity of traditional meetings has lead to the increasing technological support to group collaboration, by means of Group Support Systems (GSS/GDSS), which was designed to improve the efficiency and effectiveness of group work by offering a variety of tools to assist the group in the structuring of activities, generating ideas and improving group communication. Despite the potential GSS has to provide great benefit to groups, GSS has not diffused widely in organizations. Experience and theory shows that implementing technology alone seldom is the answer to effective and efficient collaboration. Facilitation is one of the key success factors for effective electronic meetings. Despite the importance of facilitation to the success of GSS applications, most technology developments in the past did not focus on the facilitator. Only recently is research taking the direction of supporting the facilitator for three potential reasons:①the facilitator may be a bottleneck for the widespread diffusion of GSS;②increasingly use the distributed GSS, which are more difficult than face-to-face meetings for both participants and the facilitator; and③Facilitation is complex social-technology task, which need the knowledge of GSS and the group dynamics.
Facilitation is a dynamic process that involves managing relationships between people, tasks and technology, as well as structuring tasks and contributing to the effective accomplishment of the meeting’s outcome. It is an effect way to design and develop some suit tools to support facilitator to reduce complexity of facilitation. This dissertation argues that IT-based tools will improve the performance of facilitation. We provide a framework of how to sense, understand and respond, develop some tools, and then design some experiments to prove that these tools will enhance the ability of facilitator. The main contents and conclusions of this dissertation are listed as followed:
1. Group members reach outside their boundaries, the need for computer-mediated collaboration increases. Previous researches focus on the small, face-to-face group meeting, which may be not able to support complex tasks. In a variety of domains, people develop routines to cope with complexity. In order to improve the ability of solving complex tasks and their productivity, and then derive more value from the GASS we design a conceptual framework for solving complex tasks based on group argument support systems (GASS), which divides the decision-making process into six phases based on the cognitive process of management and the skills & knowledge needed: generating motions, motions to tasks, tasks cognition & decomposition, sub-tasks to issues, issues solving and final decision-making.
2. Facilitation is one of the key success factors for effective electronic meetings. However, facilitation is a very complex task requiring high experience on social dynamics and also a person knowledgeable of the GSS technology and the facilitator may be a bottleneck for the widespread diffusion of GSS. Hence, the requirement to develop effective support for the facilitator becomes critical. Firstly, this paper presented the conceptual framework of GASS, then designed a system to support the facilitator in the full meeting life cycle based on the GASS, and the implement alternatives for each module was discussed.
3. Group argument support systems(GASS) is a effective support tool to gather public intelligence and form common wisdom. Weighting is an important hub to achieve conversion from qualitative to quantitative. In the context of public decision-making, in order to give the weight of the argument members in the open and loose structure of the organization, we analysis the new requirement and the limitation of the traditional methods, and then based on the weighting of position and the weighting of specialty, design the weighting of argument performance, which works as the periodic modify of the argument members’weighting. Experiment results indicate that the model has a precision of 80% and it is an effect indicator of the comments’value.
4. Time and consensus are two important factors in the process of group decision. In this paper, an intelligent visualization technology to evaluating, forecasting and analyzing consensus is presented. On the base of strictly analyzing and designing the attributes, the structure and the relationships of argument information, according to semantic relationship, we advance the conception of consensus point aggregate, branching point aggregate, disputed point aggregate, and integrate four Indies of the consensus level and the consensus status, attention level and the attention status, consensus level trend, attention level trend, to build the model of intelligent visualization, then design and implement the visualization system, which based on the web, using the technology of Java & xml. Finally, using an example demonstrates the application of the visualization system, and designing a experiment to analyze the effect of intelligent visualization.
5. In Group Argument Support Systems (GASS), the characteristics of parallel and anonymous data entry often result in Information overload and knowledge breakout while improving group performance. This research presented a automatic topic clustering tool to enhance participants’cognitive ability. First, we identified some challenges to automatic textual clustering. Then, we briefly reviewed the relative technologies, and described a textual analysis method involving Chinese segment, stop list and effective terms identification. Third, proposing a topic analysis method to obtain eigenvector. Fourth, using java, we designed and implemented a automatic clustering tool based on the self-Organization Map. Experiment indicated that the tool can achieve clustering recall of 0.35, clustering precision of 0.28 and clustering error of 0.83. Finally, we gave some discussions and future directions.
协助是一个动态过程,包括管理人、任务和技术之间的关系,组织任务,以及促成会议有效达成目标等方面的辅助工作。设计有效的协助支持技术,通过合适的技术手段降低主持人的协助负担是一个有效的途径。本文正是基于这样一个思路,通过IT技术降低主持人的认知负担并提高协助效率,提供了一个如何识别群体的研讨状态并做出反应的框架,开发了多项工具,并设计实验证明了这些工具的效果。
本论文的主要工作包括以下几个方面:
1.提出了一个面向解决复杂任务的群体支持系统的概念框架。该概念框架从两个级别管理决策任务:决策任务的管理和群体任务的管理;根据认知过程和各个任务需要的知识及技术,将决策过程分为六个阶段:生成议案、任务识别、任务认知与分解、生成方案、方案选择与进度安排、方案执行与反馈。同时,我们设计了多个工具来支持群体协作。对于决策任务的每个阶段,选择不同的工具集合来支持不同的群体任务。该框架可以降低任务复杂性,辅助任务的分配和人员安排。
2.基于GASS的概念框架,给出了主持人支持系统的系统结构。并基于解决复杂问题的Cynefin框架,从群体交互信息和研讨文本两个角度,识别出了共识水平与状态、关注水平与状态、群体贡献率、群体参与水平四个指标,设计并实现了文本聚类和摘要技术,形成了“感知—理解—响应”的概念结构,辅助主持人设计干涉技术,并选择适当的协助工具。
3.通过分析开放持续公共决策环境下对权重的新的需求及现有权重确定方法的不足,提出了一种群体成员权重确定方法:根据背景信息得到的职能权重和专业权重,作为群体成员的基础权重,并周期性的根据群体的参与意愿、主题把握能力以及发言质量计算研讨绩效权重,作为基础权重的修正。实验表明通过该模型可以达到80%的准确性,即能够作为研讨用户信息质量的一个有效测度。
4.在界定研讨信息属性、定义信息结构及其关系的基础上,按照语义关系,提出共识点、分歧点和争议点的概念,结合共识水平及共识状态、关注水平及关注状态、共识水平变化趋势、关注水平变化趋势四个指标,建立智能可视化模型,并用Java和XML技术设计并实现了基于Web的共识评价、预测及分析智能可视化。以一个实例给出了以人-机结合的系统思想为指导的共识评价和预测方法以及通过共识分析,形成群体注意力聚焦的示范应用。最后用实验的方法分析了智能可视化的应用效果。
5.识别了GASS环境下自动化主题聚类的一些挑战,在简要综述相关技术的基础上,结合GASS的研讨模式、研讨文本特征及中文文本分析的要求,给出了中文分词、停词表处理以及有效词语识别的文本分析技术。提出基于主题分析的特征向量选择方法,并基于自组织映射的神经网络(Self-Organization Map,SOM)思想,用Java语言设计并开发了一个自动聚类工具。实验表明,该工具可以达到0.28的聚类准确率,0.35的聚类全面率,产生0.83的聚类错误率。最后讨论了实验结果,并给出了进一步的研究方向。
The physical dispersion of current organizations, escalating complexity of problems and poor productivity of traditional meetings has lead to the increasing technological support to group collaboration, by means of Group Support Systems (GSS/GDSS), which was designed to improve the efficiency and effectiveness of group work by offering a variety of tools to assist the group in the structuring of activities, generating ideas and improving group communication. Despite the potential GSS has to provide great benefit to groups, GSS has not diffused widely in organizations. Experience and theory shows that implementing technology alone seldom is the answer to effective and efficient collaboration. Facilitation is one of the key success factors for effective electronic meetings. Despite the importance of facilitation to the success of GSS applications, most technology developments in the past did not focus on the facilitator. Only recently is research taking the direction of supporting the facilitator for three potential reasons:①the facilitator may be a bottleneck for the widespread diffusion of GSS;②increasingly use the distributed GSS, which are more difficult than face-to-face meetings for both participants and the facilitator; and③Facilitation is complex social-technology task, which need the knowledge of GSS and the group dynamics.
Facilitation is a dynamic process that involves managing relationships between people, tasks and technology, as well as structuring tasks and contributing to the effective accomplishment of the meeting’s outcome. It is an effect way to design and develop some suit tools to support facilitator to reduce complexity of facilitation. This dissertation argues that IT-based tools will improve the performance of facilitation. We provide a framework of how to sense, understand and respond, develop some tools, and then design some experiments to prove that these tools will enhance the ability of facilitator. The main contents and conclusions of this dissertation are listed as followed:
1. Group members reach outside their boundaries, the need for computer-mediated collaboration increases. Previous researches focus on the small, face-to-face group meeting, which may be not able to support complex tasks. In a variety of domains, people develop routines to cope with complexity. In order to improve the ability of solving complex tasks and their productivity, and then derive more value from the GASS we design a conceptual framework for solving complex tasks based on group argument support systems (GASS), which divides the decision-making process into six phases based on the cognitive process of management and the skills & knowledge needed: generating motions, motions to tasks, tasks cognition & decomposition, sub-tasks to issues, issues solving and final decision-making.
2. Facilitation is one of the key success factors for effective electronic meetings. However, facilitation is a very complex task requiring high experience on social dynamics and also a person knowledgeable of the GSS technology and the facilitator may be a bottleneck for the widespread diffusion of GSS. Hence, the requirement to develop effective support for the facilitator becomes critical. Firstly, this paper presented the conceptual framework of GASS, then designed a system to support the facilitator in the full meeting life cycle based on the GASS, and the implement alternatives for each module was discussed.
3. Group argument support systems(GASS) is a effective support tool to gather public intelligence and form common wisdom. Weighting is an important hub to achieve conversion from qualitative to quantitative. In the context of public decision-making, in order to give the weight of the argument members in the open and loose structure of the organization, we analysis the new requirement and the limitation of the traditional methods, and then based on the weighting of position and the weighting of specialty, design the weighting of argument performance, which works as the periodic modify of the argument members’weighting. Experiment results indicate that the model has a precision of 80% and it is an effect indicator of the comments’value.
4. Time and consensus are two important factors in the process of group decision. In this paper, an intelligent visualization technology to evaluating, forecasting and analyzing consensus is presented. On the base of strictly analyzing and designing the attributes, the structure and the relationships of argument information, according to semantic relationship, we advance the conception of consensus point aggregate, branching point aggregate, disputed point aggregate, and integrate four Indies of the consensus level and the consensus status, attention level and the attention status, consensus level trend, attention level trend, to build the model of intelligent visualization, then design and implement the visualization system, which based on the web, using the technology of Java & xml. Finally, using an example demonstrates the application of the visualization system, and designing a experiment to analyze the effect of intelligent visualization.
5. In Group Argument Support Systems (GASS), the characteristics of parallel and anonymous data entry often result in Information overload and knowledge breakout while improving group performance. This research presented a automatic topic clustering tool to enhance participants’cognitive ability. First, we identified some challenges to automatic textual clustering. Then, we briefly reviewed the relative technologies, and described a textual analysis method involving Chinese segment, stop list and effective terms identification. Third, proposing a topic analysis method to obtain eigenvector. Fourth, using java, we designed and implemented a automatic clustering tool based on the self-Organization Map. Experiment indicated that the tool can achieve clustering recall of 0.35, clustering precision of 0.28 and clustering error of 0.83. Finally, we gave some discussions and future directions.
引文
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