{"title":"群体论证思想的可视化聚类","authors":"Bin Luo, Xijin J. Tang","doi":"10.1109/WI-IAT.2010.280","DOIUrl":null,"url":null,"abstract":"This paper addresses visualized clustering methods that are embedded in CorMap and iView analysis of ideas towards the concerned topic. K-means clustering, automatic affinity diagram (KJ method) and self-organizing map are applied to CorMap analysis and graph clustering algorithm is applied to iView analysis are introduced. We report the visualized clustering results of workshops of a famous scientific forum, show the features of each clustering and compare their performance.","PeriodicalId":340211,"journal":{"name":"2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Visualized Clustering of Ideas for Group Argumentation\",\"authors\":\"Bin Luo, Xijin J. Tang\",\"doi\":\"10.1109/WI-IAT.2010.280\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper addresses visualized clustering methods that are embedded in CorMap and iView analysis of ideas towards the concerned topic. K-means clustering, automatic affinity diagram (KJ method) and self-organizing map are applied to CorMap analysis and graph clustering algorithm is applied to iView analysis are introduced. We report the visualized clustering results of workshops of a famous scientific forum, show the features of each clustering and compare their performance.\",\"PeriodicalId\":340211,\"journal\":{\"name\":\"2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-08-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WI-IAT.2010.280\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WI-IAT.2010.280","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Visualized Clustering of Ideas for Group Argumentation
This paper addresses visualized clustering methods that are embedded in CorMap and iView analysis of ideas towards the concerned topic. K-means clustering, automatic affinity diagram (KJ method) and self-organizing map are applied to CorMap analysis and graph clustering algorithm is applied to iView analysis are introduced. We report the visualized clustering results of workshops of a famous scientific forum, show the features of each clustering and compare their performance.
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