| 群体研讨中的共识分析和评价技术 |
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| 引用本文： | 谭俊峰,张朋柱,程少川,孔彬.群体研讨中的共识分析和评价技术[J].系统管理学报,2005,14(1):55-61. |
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| 作者姓名： | 谭俊峰 张朋柱 程少川 孔彬 |
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| 作者单位： | 1. 西安交通大学,管理学院,西安,710049
2. 上海交通大学,安泰管理学院,上海,200052 |
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| 基金项目： | 国家自然科学基金重大资助项目(79990580)，国家自然科学基金资助项目(70271024) |
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| 摘 要： | 实时、准确地对共识状态做出分析和评价是在综合集成研讨厅中组织好群体研讨的重要前提。为此,提出了一种称之为CAI的群体研讨中的共识分析和评价技术。依据CAI开发的软件能够根据发言之间的语义关系和研讨人的权重自动识别出共识状态,而用户可以依据CAI识别的结果干预研讨进程以便提高研讨的效率和有效性;同时,CAI软件还能够在用户的指导下学习从而增强其适应性。讨论了CAI的应用环境、分析模型、实现方法,并说明了CAI软件的工作过程和性能测试结果。
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| 关 键 词： | 综合集成研讨厅 研讨 共识 群体支持系统 人工神经网络 |
| 文章编号： | 1005-2542(2005)01-0055-07 |
| 修稿时间： | 2004年5月20日 |
Analyzing and Identifying Consensus in Group Argumentation |
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| TAN Jun-feng,ZHANG Peng-zhu,CHENG Shao-chuan,KONG Bin.Analyzing and Identifying Consensus in Group Argumentation[J].Systems Engineering Theory·Methodology·Applications,2005,14(1):55-61. |
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| Authors: | TAN Jun-feng ZHANG Peng-zhu CHENG Shao-chuan KONG Bin |
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| Institution: | TAN Jun-feng~1,ZHANG Peng-zhu~2,CHENG Shao-chuan~1,KONG Bin~1 |
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| Abstract: | It is important to discern the consensus state in real time and correctly in organizing group argumentation in Hall for Workshop of Metasynthetic Engineering. A technology to analyse and identify consensus in group argumentation, named CAI, is presented by the authors. The software based on CAI can discern automatically the consensus state according to the semantic relationships among the comments generated in the argumentation and the weights of the group members. And the users can control and adjust the argumentation process according to the result reported by the CAI software in order to improve the efficiency and effectiveness of the argumentation. The CAI software can learn new consensus modes supervised by users so that its applicability is enhanced. This paper discusses the application environment, analytical model and realization method of CAI. The working process and performance test result of the CAI software are also reported. |
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| Keywords: | hall for workshop of metasynthetic engineering argumentation consensus group support systems artificial neural networks |
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