MS 워드 
목차
Abstract1. Introduction
2. Literature review
2.1 Vector-space model
2.2 Automatic document classification
3. The interactive methodoloy for idea categorizing
3.1 Overview of the methodology
3.2 Idea indexing using keywords and its affinity
3.3 Generating weighted idea matrix
3.4 Generating similarity matrix
3.5 Interactive clustering
4. Prototyping and experiments
4.1 Architecture of IIC
4.2 Experiments
V. Conclusions
References
본문내용
Research on group decisions and EMS have been increasing rapidly according to the widespread of Internet technology. Idea categorizing used at existing group decision support systems was resulted in tacking as long in idea categorizing as it does for idea generating, clustering an idea in multiple categories, and identifying almost similar redundant categories. However such methods have critical limitation in the electronic meeting systems, we suggest an intelligent idea categorizing methodology which is a bottom-up approach. This method consists of steps to present idea using keywords, identifying keywords’ affinity, computing similarity among ideas, and clustering ideas. We also developed a prototype system, intelligent idea categorizer and evaluated its performance using the comparision experimetn with other systems.참고 자료
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