{"title":"与SQL数据库集成数据挖掘:用于数据挖掘的OLE DB","authors":"Amir Netz, S. Chaudhuri, U. Fayyad, J. Bernhardt","doi":"10.1109/ICDE.2001.914850","DOIUrl":null,"url":null,"abstract":"The integration of data mining with traditional database systems is key to making it convenient, easy to deploy in real applications, and to growing its user base. We describe the new API for data mining proposed by Microsoft as extensions to the OLE DB standard. We illustrate the basic notions that motivated the API's design and describe the key components of an OLE DB for the data mining provider. We also include examples of the usage and treat the problems of data representation and integration with the SQL framework. We believe this new API will go a long way in enabling deployment of data mining in enterprise data warehouses. A reference implementation of a provider is available with the recent release of Microsoft SQL Server 2000 database system.","PeriodicalId":431818,"journal":{"name":"Proceedings 17th International Conference on Data Engineering","volume":"2 8","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"84","resultStr":"{\"title\":\"Integrating data mining with SQL databases: OLE DB for data mining\",\"authors\":\"Amir Netz, S. Chaudhuri, U. Fayyad, J. Bernhardt\",\"doi\":\"10.1109/ICDE.2001.914850\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The integration of data mining with traditional database systems is key to making it convenient, easy to deploy in real applications, and to growing its user base. We describe the new API for data mining proposed by Microsoft as extensions to the OLE DB standard. We illustrate the basic notions that motivated the API's design and describe the key components of an OLE DB for the data mining provider. We also include examples of the usage and treat the problems of data representation and integration with the SQL framework. We believe this new API will go a long way in enabling deployment of data mining in enterprise data warehouses. A reference implementation of a provider is available with the recent release of Microsoft SQL Server 2000 database system.\",\"PeriodicalId\":431818,\"journal\":{\"name\":\"Proceedings 17th International Conference on Data Engineering\",\"volume\":\"2 8\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-04-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"84\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings 17th International Conference on Data Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDE.2001.914850\",\"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 17th International Conference on Data Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDE.2001.914850","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 84
摘要
数据挖掘与传统数据库系统的集成是使其方便、易于在实际应用程序中部署以及扩大其用户基础的关键。我们将微软提出的用于数据挖掘的新API描述为OLE DB标准的扩展。我们说明了激发API设计的基本概念,并描述了数据挖掘提供者的OLE DB的关键组件。我们还包括使用示例,并处理数据表示和与SQL框架集成的问题。我们相信这个新的API将在企业数据仓库中部署数据挖掘方面大有帮助。最近发布的Microsoft SQL Server 2000数据库系统提供了提供程序的参考实现。
Integrating data mining with SQL databases: OLE DB for data mining
The integration of data mining with traditional database systems is key to making it convenient, easy to deploy in real applications, and to growing its user base. We describe the new API for data mining proposed by Microsoft as extensions to the OLE DB standard. We illustrate the basic notions that motivated the API's design and describe the key components of an OLE DB for the data mining provider. We also include examples of the usage and treat the problems of data representation and integration with the SQL framework. We believe this new API will go a long way in enabling deployment of data mining in enterprise data warehouses. A reference implementation of a provider is available with the recent release of Microsoft SQL Server 2000 database system.