{"title":"基于潜在投影的文档聚类检测","authors":"Dora Alvarez-Medina, H. Hidalgo-Silva","doi":"10.1109/ICDIM.2009.5356765","DOIUrl":null,"url":null,"abstract":"Probabilistic text data modeling is usually considered with Bernoulli or multinomial event models. The main problem of text mining is the large amount of zero account in the matrix representation. Recently a document visualization technique incorporating the Zero Inflated Poisson model in the Generative Topographic Mapping algorithm has been proposed. This probabilistic model can be applied as a text document visualization tool. In this work, an algorithm for automatically extracting the clusters in the visualization results is presented. The combination of visualization-cluster extraction algorithms allows to obtain and evaluate document collections. Several results are presented for 20-Newsgroups and Reuters data.","PeriodicalId":300287,"journal":{"name":"2009 Fourth International Conference on Digital Information Management","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Document cluster detection on latent projections\",\"authors\":\"Dora Alvarez-Medina, H. Hidalgo-Silva\",\"doi\":\"10.1109/ICDIM.2009.5356765\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Probabilistic text data modeling is usually considered with Bernoulli or multinomial event models. The main problem of text mining is the large amount of zero account in the matrix representation. Recently a document visualization technique incorporating the Zero Inflated Poisson model in the Generative Topographic Mapping algorithm has been proposed. This probabilistic model can be applied as a text document visualization tool. In this work, an algorithm for automatically extracting the clusters in the visualization results is presented. The combination of visualization-cluster extraction algorithms allows to obtain and evaluate document collections. Several results are presented for 20-Newsgroups and Reuters data.\",\"PeriodicalId\":300287,\"journal\":{\"name\":\"2009 Fourth International Conference on Digital Information Management\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-12-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Fourth International Conference on Digital Information Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDIM.2009.5356765\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Fourth International Conference on Digital Information Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDIM.2009.5356765","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Probabilistic text data modeling is usually considered with Bernoulli or multinomial event models. The main problem of text mining is the large amount of zero account in the matrix representation. Recently a document visualization technique incorporating the Zero Inflated Poisson model in the Generative Topographic Mapping algorithm has been proposed. This probabilistic model can be applied as a text document visualization tool. In this work, an algorithm for automatically extracting the clusters in the visualization results is presented. The combination of visualization-cluster extraction algorithms allows to obtain and evaluate document collections. Several results are presented for 20-Newsgroups and Reuters data.