{"title":"从多决策有序信息表中提取规则","authors":"Bin Shen, Min Yao, Zhaohui Wu","doi":"10.1109/ICDMW.2008.75","DOIUrl":null,"url":null,"abstract":"Ordered information table is one of the most important research areas of granular computing. In this thesis, we introduce multiple decisions ordered information tables based on the concept of ordered information tables. Multiple decisions ordered information tables are used to describe the actual multiple decision attributes situation of reality. We study the process of rule extraction from multiple decisions ordered information tables thoroughly and several concepts about this process are proposed and discussed. At last, an example of multiple decisions ordered information tables is used to illustrate the basic ideas. These ideas and methods are quite useful for KDD, DM and GC.","PeriodicalId":175955,"journal":{"name":"2008 IEEE International Conference on Data Mining Workshops","volume":"148 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Rules Extraction from Multiple Decisions Ordered Information Tables\",\"authors\":\"Bin Shen, Min Yao, Zhaohui Wu\",\"doi\":\"10.1109/ICDMW.2008.75\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Ordered information table is one of the most important research areas of granular computing. In this thesis, we introduce multiple decisions ordered information tables based on the concept of ordered information tables. Multiple decisions ordered information tables are used to describe the actual multiple decision attributes situation of reality. We study the process of rule extraction from multiple decisions ordered information tables thoroughly and several concepts about this process are proposed and discussed. At last, an example of multiple decisions ordered information tables is used to illustrate the basic ideas. These ideas and methods are quite useful for KDD, DM and GC.\",\"PeriodicalId\":175955,\"journal\":{\"name\":\"2008 IEEE International Conference on Data Mining Workshops\",\"volume\":\"148 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-12-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 IEEE International Conference on Data Mining Workshops\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDMW.2008.75\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE International Conference on Data Mining Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDMW.2008.75","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Rules Extraction from Multiple Decisions Ordered Information Tables
Ordered information table is one of the most important research areas of granular computing. In this thesis, we introduce multiple decisions ordered information tables based on the concept of ordered information tables. Multiple decisions ordered information tables are used to describe the actual multiple decision attributes situation of reality. We study the process of rule extraction from multiple decisions ordered information tables thoroughly and several concepts about this process are proposed and discussed. At last, an example of multiple decisions ordered information tables is used to illustrate the basic ideas. These ideas and methods are quite useful for KDD, DM and GC.
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