属性(特征)补全——来自数据挖掘前景的属性理论

2002 IEEE International Conference on Data Mining, 2002. Proceedings. Pub Date : 2002-12-09 DOI:10.1109/ICDM.2002.1183914

T. Lin

{"title":"属性(特征)补全——来自数据挖掘前景的属性理论","authors":"T. Lin","doi":"10.1109/ICDM.2002.1183914","DOIUrl":null,"url":null,"abstract":"A \"correct\" selection of attributes (features) is vital in data mining. As a first step, this paper constructs all possible attributes of a given relation. The results are based on the observations that each relation is isomorphic to a unique abstract relation, called a canonical model. The complete set of attributes of the canonical model is, then, constructed. Any attribute of a relation can be interpreted (via isomorphism) from such a complete set.","PeriodicalId":405340,"journal":{"name":"2002 IEEE International Conference on Data Mining, 2002. Proceedings.","volume":"41 5","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"33","resultStr":"{\"title\":\"Attribute (feature) completion - the theory of attributes from data mining prospect\",\"authors\":\"T. Lin\",\"doi\":\"10.1109/ICDM.2002.1183914\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A \\\"correct\\\" selection of attributes (features) is vital in data mining. As a first step, this paper constructs all possible attributes of a given relation. The results are based on the observations that each relation is isomorphic to a unique abstract relation, called a canonical model. The complete set of attributes of the canonical model is, then, constructed. Any attribute of a relation can be interpreted (via isomorphism) from such a complete set.\",\"PeriodicalId\":405340,\"journal\":{\"name\":\"2002 IEEE International Conference on Data Mining, 2002. Proceedings.\",\"volume\":\"41 5\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-12-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"33\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2002 IEEE International Conference on Data Mining, 2002. Proceedings.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDM.2002.1183914\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2002 IEEE International Conference on Data Mining, 2002. Proceedings.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDM.2002.1183914","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 33

摘要

“正确”选择属性(特征)在数据挖掘中是至关重要的。作为第一步，本文构造了给定关系的所有可能属性。这些结果是基于观察到的，即每个关系都与一个唯一的抽象关系同构，称为规范模型。然后，构造规范模型的完整属性集。关系的任何属性都可以(通过同构)从这样一个完备集解释。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Attribute (feature) completion - the theory of attributes from data mining prospect

A "correct" selection of attributes (features) is vital in data mining. As a first step, this paper constructs all possible attributes of a given relation. The results are based on the observations that each relation is isomorphic to a unique abstract relation, called a canonical model. The complete set of attributes of the canonical model is, then, constructed. Any attribute of a relation can be interpreted (via isomorphism) from such a complete set.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2002 IEEE International Conference on Data Mining, 2002. Proceedings.

自引率

0.00%

发文量