{"title":"基于信息熵测度虚拟社区知识扩散的新模型","authors":"Xiangyu Wang, Junwang, Ou Liu","doi":"10.1109/ICSSSM.2015.7170170","DOIUrl":null,"url":null,"abstract":"In order to measure the different values of a great number of knowledge spreading in virtual communities, we build a knowledge diffusion measurement model based on information entropy. The model quantifies the knowledge entropy of different nodes in the spreading process in terms of users' behaviors. Consequently, transmitted knowledge can be sorted by the knowledge entropy, making the measurement of knowledge values and knowledge diffusion more accurately.","PeriodicalId":211783,"journal":{"name":"2015 12th International Conference on Service Systems and Service Management (ICSSSM)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A new model to measure the knowledge diffusion via information entropy in virtual communities\",\"authors\":\"Xiangyu Wang, Junwang, Ou Liu\",\"doi\":\"10.1109/ICSSSM.2015.7170170\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to measure the different values of a great number of knowledge spreading in virtual communities, we build a knowledge diffusion measurement model based on information entropy. The model quantifies the knowledge entropy of different nodes in the spreading process in terms of users' behaviors. Consequently, transmitted knowledge can be sorted by the knowledge entropy, making the measurement of knowledge values and knowledge diffusion more accurately.\",\"PeriodicalId\":211783,\"journal\":{\"name\":\"2015 12th International Conference on Service Systems and Service Management (ICSSSM)\",\"volume\":\"52 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-06-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 12th International Conference on Service Systems and Service Management (ICSSSM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSSSM.2015.7170170\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 12th International Conference on Service Systems and Service Management (ICSSSM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSSSM.2015.7170170","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A new model to measure the knowledge diffusion via information entropy in virtual communities
In order to measure the different values of a great number of knowledge spreading in virtual communities, we build a knowledge diffusion measurement model based on information entropy. The model quantifies the knowledge entropy of different nodes in the spreading process in terms of users' behaviors. Consequently, transmitted knowledge can be sorted by the knowledge entropy, making the measurement of knowledge values and knowledge diffusion more accurately.