{"title":"Data mining","authors":"C. Olaru, L. Wehenkel","doi":"10.4018/978-1-59140-051-6","DOIUrl":null,"url":null,"abstract":"Data mining (DM) is a folkloric denomination of a complex activity that aims at extracting synthesized and previously unknown information from large databases. It denotes also a multidisciplinary field of research and development of algorithms and software environments to support this activity in the context of real-life problems where often huge amounts of data are available for mining. There is a lot of publicity in this field and also different ways to see the things. Hence, depending on the viewpoints, DM is sometimes considered as just a step in a broader overall process called knowledge discovery in databases (KDD), or as a synonym of the latter. This tutorial presents the concept of data mining and aims at providing an understanding of the overall process and tools involved: how the process turns out, what can be done with it, what are the main techniques behind it, and which are the operational aspects. The tutorial also describes a few examples of data mining applications, so as to motivate the power system field as a very opportune data mining application.","PeriodicalId":435675,"journal":{"name":"IEEE Computer Applications in Power","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1999-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"46","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Computer Applications in Power","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/978-1-59140-051-6","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 46
Abstract
Data mining (DM) is a folkloric denomination of a complex activity that aims at extracting synthesized and previously unknown information from large databases. It denotes also a multidisciplinary field of research and development of algorithms and software environments to support this activity in the context of real-life problems where often huge amounts of data are available for mining. There is a lot of publicity in this field and also different ways to see the things. Hence, depending on the viewpoints, DM is sometimes considered as just a step in a broader overall process called knowledge discovery in databases (KDD), or as a synonym of the latter. This tutorial presents the concept of data mining and aims at providing an understanding of the overall process and tools involved: how the process turns out, what can be done with it, what are the main techniques behind it, and which are the operational aspects. The tutorial also describes a few examples of data mining applications, so as to motivate the power system field as a very opportune data mining application.