{"title":"基于投影寻踪模型的中文文本挖掘新方法","authors":"Xinqing Geng, Zongmin Ma","doi":"10.1109/WARTIA.2014.6976431","DOIUrl":null,"url":null,"abstract":"A new fuzzy clustering algorithm (PPC) based on project pursuit model is presented in the paper. The main defect of the traditional clustering algorithm is to reduce dimension, while PPC don't need reduce dimension. Firstly, the text vector is normalized; Secondly, the project index function is constructed; Thirdly, the project function is optimized; Finally, the clustering result is acquired according to classification threshold. PPC algorithm improves the efficiency and precision of clustering.","PeriodicalId":288854,"journal":{"name":"2014 IEEE Workshop on Advanced Research and Technology in Industry Applications (WARTIA)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"PPC:A novel approach of Chinese text mining based on Projection pursuit model\",\"authors\":\"Xinqing Geng, Zongmin Ma\",\"doi\":\"10.1109/WARTIA.2014.6976431\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A new fuzzy clustering algorithm (PPC) based on project pursuit model is presented in the paper. The main defect of the traditional clustering algorithm is to reduce dimension, while PPC don't need reduce dimension. Firstly, the text vector is normalized; Secondly, the project index function is constructed; Thirdly, the project function is optimized; Finally, the clustering result is acquired according to classification threshold. PPC algorithm improves the efficiency and precision of clustering.\",\"PeriodicalId\":288854,\"journal\":{\"name\":\"2014 IEEE Workshop on Advanced Research and Technology in Industry Applications (WARTIA)\",\"volume\":\"71 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE Workshop on Advanced Research and Technology in Industry Applications (WARTIA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WARTIA.2014.6976431\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE Workshop on Advanced Research and Technology in Industry Applications (WARTIA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WARTIA.2014.6976431","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
PPC:A novel approach of Chinese text mining based on Projection pursuit model
A new fuzzy clustering algorithm (PPC) based on project pursuit model is presented in the paper. The main defect of the traditional clustering algorithm is to reduce dimension, while PPC don't need reduce dimension. Firstly, the text vector is normalized; Secondly, the project index function is constructed; Thirdly, the project function is optimized; Finally, the clustering result is acquired according to classification threshold. PPC algorithm improves the efficiency and precision of clustering.