{"title":"基于模糊ART神经网络的混合源文档聚类系统","authors":"M. Rojček, I. Mokris","doi":"10.1109/ICSSE.2013.6614670","DOIUrl":null,"url":null,"abstract":"The article presents a model for text document clustering based on Fuzzy ART neural network with two separate network segments. The first segment (Internet) enables clustering for the classification of documents into new categories, and the second segment (intranet) enables the modified Fuzzy ART algorithm to assign documents into existing categories. The article observe behavior of the model based on Fuzzy ART network, into which entering the different strategies in the different segments of synthetic text documents.","PeriodicalId":124317,"journal":{"name":"2013 International Conference on System Science and Engineering (ICSSE)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"System for document clustering from mixed sources based on Fuzzy ART neural network\",\"authors\":\"M. Rojček, I. Mokris\",\"doi\":\"10.1109/ICSSE.2013.6614670\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The article presents a model for text document clustering based on Fuzzy ART neural network with two separate network segments. The first segment (Internet) enables clustering for the classification of documents into new categories, and the second segment (intranet) enables the modified Fuzzy ART algorithm to assign documents into existing categories. The article observe behavior of the model based on Fuzzy ART network, into which entering the different strategies in the different segments of synthetic text documents.\",\"PeriodicalId\":124317,\"journal\":{\"name\":\"2013 International Conference on System Science and Engineering (ICSSE)\",\"volume\":\"43 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-07-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 International Conference on System Science and Engineering (ICSSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSSE.2013.6614670\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Conference on System Science and Engineering (ICSSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSSE.2013.6614670","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
System for document clustering from mixed sources based on Fuzzy ART neural network
The article presents a model for text document clustering based on Fuzzy ART neural network with two separate network segments. The first segment (Internet) enables clustering for the classification of documents into new categories, and the second segment (intranet) enables the modified Fuzzy ART algorithm to assign documents into existing categories. The article observe behavior of the model based on Fuzzy ART network, into which entering the different strategies in the different segments of synthetic text documents.
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