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基于案例推理的网络舆情辅助决策系统研究
引用本文:陈祥,洪福金,张贤坤.基于案例推理的网络舆情辅助决策系统研究[J].计算机与现代化,2012(6):13-16.
作者姓名:陈祥  洪福金  张贤坤
作者单位:1. 安徽省芜湖县广播电视台,安徽芜湖,241100
2. 安徽省芜湖县国土资源局,安徽芜湖,241100
3. 天津科技大学计算机科学与信息工程学院,天津,300222
基金项目:天津市科技型中小企业技术创新基金资助项目
摘    要:为了实现网络舆情监测与辅助决策,提出一种基于案例推理的网络舆情辅助决策系统框架。首先综述网络舆情研究现状,提出基于案例推理的网络舆情辅助决策系统的意义;其次,研究基于案例推理的网络舆情辅助决策系统的工作流程,并提出基于案例推理的网络舆情辅助决策系统的框架;接着研究基于案例推理的网络舆情辅助决策系统中的关键内容,即案例表示与检索,并给出详细实现方法;最后,在以上研究基础上实现原型系统,结果表明该系统可以有效实现舆情辅助决策。

关 键 词:网络舆情  案例推理  案例表示  案例检索  相似度

Research on Aided Decision System of Internet Public Opinion Based on CBR
CHEN Xiang , HONG Fu-jin , ZHANG Xian-kun.Research on Aided Decision System of Internet Public Opinion Based on CBR[J].Computer and Modernization,2012(6):13-16.
Authors:CHEN Xiang  HONG Fu-jin  ZHANG Xian-kun
Affiliation:1. Television Station of Wuhu County of Anhui Province, Wuhu 241100, China; 2. Land and Resources Bureau of Wuhu County of Anhui Province, Wuhu 241100, China; 3. School of Computer Science and Information Engineering, Tianjin University of Science and Technology, Tianjin 300222, China)
Abstract:In order to meet the need of monitoring and aided decision of internet public opinion, a ease-based reasoning (CBR) framework for aided decision system of internet public opinion is proposed. Firstly, a survey of study on intemet public opinion is made, and the significance of research for aided decision system of internet public opinion based on CBR is given ; secondly, the workflow of aided decision system of intemet public opinion based on CBR is analyzed, and the framework for aided decision sys- tem of internet public opinion based on CBR is proposed; then the key elements of aided decision system of internet public opin- ion based on CBR are analyzed, such as case representation and case retrieval, and the implementation methods of them are given in detail; finaUy, a prototype system based on the above is shown, and experimental results show that it is efficient to realize the aided decisions with this system.
Keywords:internet public opinion  case-based reasoning (CBR)  case representation  case retrieval  similarity degree
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