{"title":"多数据流挖掘的研究问题","authors":"Wenyan Wu, L. Gruenwald","doi":"10.1145/1833280.1833288","DOIUrl":null,"url":null,"abstract":"There exist emerging applications of data streams that have mining requirements. Although single data stream mining has been extensively studied, little research has been done for mining multiple data streams (MDS), which are more complex than single data streams and involved in many real-world applications. This paper discusses the characteristics of MDS, proposes a formal definition for them, analyzes MDS application in terms of mining requirements, and identifies research issues for MDS mining.","PeriodicalId":383372,"journal":{"name":"StreamKDD '10","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"27","resultStr":"{\"title\":\"Research issues in mining multiple data streams\",\"authors\":\"Wenyan Wu, L. Gruenwald\",\"doi\":\"10.1145/1833280.1833288\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"There exist emerging applications of data streams that have mining requirements. Although single data stream mining has been extensively studied, little research has been done for mining multiple data streams (MDS), which are more complex than single data streams and involved in many real-world applications. This paper discusses the characteristics of MDS, proposes a formal definition for them, analyzes MDS application in terms of mining requirements, and identifies research issues for MDS mining.\",\"PeriodicalId\":383372,\"journal\":{\"name\":\"StreamKDD '10\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-07-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"27\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"StreamKDD '10\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1833280.1833288\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"StreamKDD '10","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1833280.1833288","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
There exist emerging applications of data streams that have mining requirements. Although single data stream mining has been extensively studied, little research has been done for mining multiple data streams (MDS), which are more complex than single data streams and involved in many real-world applications. This paper discusses the characteristics of MDS, proposes a formal definition for them, analyzes MDS application in terms of mining requirements, and identifies research issues for MDS mining.