{"title":"客座编辑介绍:数据挖掘","authors":"G. Karypis","doi":"10.1109/MCSE.2002.10003","DOIUrl":null,"url":null,"abstract":"Data mining is the process of automatically extracting new and useful knowledge hidden in large data sets. This emerging discipline is becoming increasingly important as advances in data collection lead to the explosive growth in the amount of available data. Data mining techniques primarily help analyze commercial data sets and play a critical role in analyzing and understanding purchasing behaviors for effective consumer relations management, process optimization, personalized marketing, and customer segmentation.","PeriodicalId":100659,"journal":{"name":"IMPACT of Computing in Science and Engineering","volume":"25 1","pages":"12-13"},"PeriodicalIF":0.0000,"publicationDate":"2002-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Guest Editor's Introduction: Data Mining\",\"authors\":\"G. Karypis\",\"doi\":\"10.1109/MCSE.2002.10003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Data mining is the process of automatically extracting new and useful knowledge hidden in large data sets. This emerging discipline is becoming increasingly important as advances in data collection lead to the explosive growth in the amount of available data. Data mining techniques primarily help analyze commercial data sets and play a critical role in analyzing and understanding purchasing behaviors for effective consumer relations management, process optimization, personalized marketing, and customer segmentation.\",\"PeriodicalId\":100659,\"journal\":{\"name\":\"IMPACT of Computing in Science and Engineering\",\"volume\":\"25 1\",\"pages\":\"12-13\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IMPACT of Computing in Science and Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MCSE.2002.10003\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IMPACT of Computing in Science and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MCSE.2002.10003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Data mining is the process of automatically extracting new and useful knowledge hidden in large data sets. This emerging discipline is becoming increasingly important as advances in data collection lead to the explosive growth in the amount of available data. Data mining techniques primarily help analyze commercial data sets and play a critical role in analyzing and understanding purchasing behaviors for effective consumer relations management, process optimization, personalized marketing, and customer segmentation.