{"title":"RuleMiner:数据质量规则发现","authors":"Xu Chu, I. Ilyas, Paolo Papotti, Yin Ye","doi":"10.1109/ICDE.2014.6816746","DOIUrl":null,"url":null,"abstract":"Integrity constraints (ICs) are valuables tools for enforcing correct application semantics. However, manually designing ICs require experts and time, hence the need for automatic discovery. Previous automatic ICs discovery suffer from (1) limited ICs language expressiveness; and (2) time-consuming manual verification of discovered ICs. We introduce RULEMINER, a system for discovering data quality rules that addresses the limitations of existing solutions.","PeriodicalId":159130,"journal":{"name":"2014 IEEE 30th International Conference on Data Engineering","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"30","resultStr":"{\"title\":\"RuleMiner: Data quality rules discovery\",\"authors\":\"Xu Chu, I. Ilyas, Paolo Papotti, Yin Ye\",\"doi\":\"10.1109/ICDE.2014.6816746\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Integrity constraints (ICs) are valuables tools for enforcing correct application semantics. However, manually designing ICs require experts and time, hence the need for automatic discovery. Previous automatic ICs discovery suffer from (1) limited ICs language expressiveness; and (2) time-consuming manual verification of discovered ICs. We introduce RULEMINER, a system for discovering data quality rules that addresses the limitations of existing solutions.\",\"PeriodicalId\":159130,\"journal\":{\"name\":\"2014 IEEE 30th International Conference on Data Engineering\",\"volume\":\"37 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-05-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"30\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE 30th International Conference on Data Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDE.2014.6816746\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE 30th International Conference on Data Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDE.2014.6816746","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Integrity constraints (ICs) are valuables tools for enforcing correct application semantics. However, manually designing ICs require experts and time, hence the need for automatic discovery. Previous automatic ICs discovery suffer from (1) limited ICs language expressiveness; and (2) time-consuming manual verification of discovered ICs. We introduce RULEMINER, a system for discovering data quality rules that addresses the limitations of existing solutions.
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