{"title":"数据挖掘在主动数据库系统规则设计中的应用","authors":"Min Dai, Ya-Lou Huang","doi":"10.1109/FSKD.2007.236","DOIUrl":null,"url":null,"abstract":"Rule design is very important for active database system implementation. But, it is also very difficult for us because of lacking methodology and support. In the paper, active rule design is regarded as a whole process and identified to three steps: rule extraction, rule analysis, and rule update. Data mining technique is originally introduced into rule design by us to cope with the problems arisen in active semantic extraction, termination analysis of rules set, and rules update. Rule mining methods are adopted to extract active semantics, and the discovered rules are used to assist active rule specification. Data mining technique is integrated with the triggering graph to improve the accuracy of termination analysis. Finally, data mining technique is used to identify new semantics and determine which rules should be updated.","PeriodicalId":201883,"journal":{"name":"Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Data Mining Used in Rule Design for Active Database Systems\",\"authors\":\"Min Dai, Ya-Lou Huang\",\"doi\":\"10.1109/FSKD.2007.236\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Rule design is very important for active database system implementation. But, it is also very difficult for us because of lacking methodology and support. In the paper, active rule design is regarded as a whole process and identified to three steps: rule extraction, rule analysis, and rule update. Data mining technique is originally introduced into rule design by us to cope with the problems arisen in active semantic extraction, termination analysis of rules set, and rules update. Rule mining methods are adopted to extract active semantics, and the discovered rules are used to assist active rule specification. Data mining technique is integrated with the triggering graph to improve the accuracy of termination analysis. Finally, data mining technique is used to identify new semantics and determine which rules should be updated.\",\"PeriodicalId\":201883,\"journal\":{\"name\":\"Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007)\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-08-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FSKD.2007.236\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FSKD.2007.236","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Data Mining Used in Rule Design for Active Database Systems
Rule design is very important for active database system implementation. But, it is also very difficult for us because of lacking methodology and support. In the paper, active rule design is regarded as a whole process and identified to three steps: rule extraction, rule analysis, and rule update. Data mining technique is originally introduced into rule design by us to cope with the problems arisen in active semantic extraction, termination analysis of rules set, and rules update. Rule mining methods are adopted to extract active semantics, and the discovered rules are used to assist active rule specification. Data mining technique is integrated with the triggering graph to improve the accuracy of termination analysis. Finally, data mining technique is used to identify new semantics and determine which rules should be updated.