{"title":"用于数据挖掘的紧密耦合架构","authors":"Rosa Meo, G. Psaila, S. Ceri","doi":"10.1109/ICDE.1998.655794","DOIUrl":null,"url":null,"abstract":"Current approaches to data mining are based on the use of a decoupled architecture, where data are first extracted from a database and then processed by a specialized data mining engine. This paper proposes instead a tightly-coupled architecture, where data mining is integrated within a classical SQL server. The premise of this work is a SQL-like operator, called MINE RULE. We show how the various syntactic features of the operator can be managed by either a SQL engine or a classical data mining engine; our main objective is to identify the border between typical relational processing, executed by the relational server, and data mining processing, executed by a specialized component. The resulting architecture exhibits portability at the SQL level and integration of inputs and outputs of the data mining operator with the database, and provides the guidelines for promoting the integration of other data mining techniques and systems with SQL servers.","PeriodicalId":264926,"journal":{"name":"Proceedings 14th International Conference on Data Engineering","volume":"78 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"39","resultStr":"{\"title\":\"A tightly-coupled architecture for data mining\",\"authors\":\"Rosa Meo, G. Psaila, S. Ceri\",\"doi\":\"10.1109/ICDE.1998.655794\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Current approaches to data mining are based on the use of a decoupled architecture, where data are first extracted from a database and then processed by a specialized data mining engine. This paper proposes instead a tightly-coupled architecture, where data mining is integrated within a classical SQL server. The premise of this work is a SQL-like operator, called MINE RULE. We show how the various syntactic features of the operator can be managed by either a SQL engine or a classical data mining engine; our main objective is to identify the border between typical relational processing, executed by the relational server, and data mining processing, executed by a specialized component. The resulting architecture exhibits portability at the SQL level and integration of inputs and outputs of the data mining operator with the database, and provides the guidelines for promoting the integration of other data mining techniques and systems with SQL servers.\",\"PeriodicalId\":264926,\"journal\":{\"name\":\"Proceedings 14th International Conference on Data Engineering\",\"volume\":\"78 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1998-02-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"39\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings 14th International Conference on Data Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDE.1998.655794\",\"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 14th International Conference on Data Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDE.1998.655794","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Current approaches to data mining are based on the use of a decoupled architecture, where data are first extracted from a database and then processed by a specialized data mining engine. This paper proposes instead a tightly-coupled architecture, where data mining is integrated within a classical SQL server. The premise of this work is a SQL-like operator, called MINE RULE. We show how the various syntactic features of the operator can be managed by either a SQL engine or a classical data mining engine; our main objective is to identify the border between typical relational processing, executed by the relational server, and data mining processing, executed by a specialized component. The resulting architecture exhibits portability at the SQL level and integration of inputs and outputs of the data mining operator with the database, and provides the guidelines for promoting the integration of other data mining techniques and systems with SQL servers.