Huiwen Fu, Dingrong Yuan, Xiaomeng Huang, Xiaohu Yang
{"title":"一种多数据库全局异常模式挖掘新方法","authors":"Huiwen Fu, Dingrong Yuan, Xiaomeng Huang, Xiaohu Yang","doi":"10.1109/ICSSEM.2012.6340825","DOIUrl":null,"url":null,"abstract":"Many large organizations need to mine multi-databases distributed in their branches for exceptional pattern for the purpose of globally decision-making. The present major strategies of mining exceptional interesting pattern is to merge all multi-databases into a single dataset for discovery, but this destructs the local distribution character of the pattern in different branches. The only work mining multi-database not as a single database is not complete and the method to find exceptional patterns is inaccuracy. In this paper, we give a new method to mining exceptional interesting pattern in multi-database. The experimental results show that our theory is practical and efficient.","PeriodicalId":115037,"journal":{"name":"2012 3rd International Conference on System Science, Engineering Design and Manufacturing Informatization","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A new method for mining globally exceptional patterns in multi-database\",\"authors\":\"Huiwen Fu, Dingrong Yuan, Xiaomeng Huang, Xiaohu Yang\",\"doi\":\"10.1109/ICSSEM.2012.6340825\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Many large organizations need to mine multi-databases distributed in their branches for exceptional pattern for the purpose of globally decision-making. The present major strategies of mining exceptional interesting pattern is to merge all multi-databases into a single dataset for discovery, but this destructs the local distribution character of the pattern in different branches. The only work mining multi-database not as a single database is not complete and the method to find exceptional patterns is inaccuracy. In this paper, we give a new method to mining exceptional interesting pattern in multi-database. The experimental results show that our theory is practical and efficient.\",\"PeriodicalId\":115037,\"journal\":{\"name\":\"2012 3rd International Conference on System Science, Engineering Design and Manufacturing Informatization\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-11-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 3rd International Conference on System Science, Engineering Design and Manufacturing Informatization\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSSEM.2012.6340825\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 3rd International Conference on System Science, Engineering Design and Manufacturing Informatization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSSEM.2012.6340825","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A new method for mining globally exceptional patterns in multi-database
Many large organizations need to mine multi-databases distributed in their branches for exceptional pattern for the purpose of globally decision-making. The present major strategies of mining exceptional interesting pattern is to merge all multi-databases into a single dataset for discovery, but this destructs the local distribution character of the pattern in different branches. The only work mining multi-database not as a single database is not complete and the method to find exceptional patterns is inaccuracy. In this paper, we give a new method to mining exceptional interesting pattern in multi-database. The experimental results show that our theory is practical and efficient.