{"title":"一个直观的框架，用于理解不断发展的数据流中的变化","authors":"C. Aggarwal","doi":"10.1109/ICDE.2002.994715","DOIUrl":null,"url":null,"abstract":"Many organizations today store large streams of transactional data in real time. This data can often show important changes in trends over time. In many commercial applications, it may be valuable to provide the user with an understanding of the nature of changes occuring over time in the data stream. In this paper, we discuss the process of analysing the significant changes and trends in data streams in a way which is understandable, intuitive and user-friendly.","PeriodicalId":191529,"journal":{"name":"Proceedings 18th International Conference on Data Engineering","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"26","resultStr":"{\"title\":\"An intuitive framework for understanding changes in evolving data streams\",\"authors\":\"C. Aggarwal\",\"doi\":\"10.1109/ICDE.2002.994715\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Many organizations today store large streams of transactional data in real time. This data can often show important changes in trends over time. In many commercial applications, it may be valuable to provide the user with an understanding of the nature of changes occuring over time in the data stream. In this paper, we discuss the process of analysing the significant changes and trends in data streams in a way which is understandable, intuitive and user-friendly.\",\"PeriodicalId\":191529,\"journal\":{\"name\":\"Proceedings 18th International Conference on Data Engineering\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-08-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"26\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings 18th International Conference on Data Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDE.2002.994715\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 18th International Conference on Data Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDE.2002.994715","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An intuitive framework for understanding changes in evolving data streams
Many organizations today store large streams of transactional data in real time. This data can often show important changes in trends over time. In many commercial applications, it may be valuable to provide the user with an understanding of the nature of changes occuring over time in the data stream. In this paper, we discuss the process of analysing the significant changes and trends in data streams in a way which is understandable, intuitive and user-friendly.
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