{"title":"数据清理和XML: DBLP体验","authors":"Wai Lup Low, W. Tok, M. Lee, T. Ling","doi":"10.1109/ICDE.2002.994723","DOIUrl":null,"url":null,"abstract":"With the increasing popularity of data-centric XML, data warehousing and mining applications are being developed for rapidly burgeoning XML data repositories. Data quality will no doubt be a critical factor for the success of such applications. Data cleaning, which refers to the processes used to improve data quality, has been well researched in the context of traditional databases. In earlier work we developed a knowledge-based framework for data cleaning relational databases. In this work, we present a novel attempt to apply this framework to XML databases. Our experimental dataset is the DBLP database, a popular online XML bibliography database used by many researchers.","PeriodicalId":191529,"journal":{"name":"Proceedings 18th International Conference on Data Engineering","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Data cleaning and XML: the DBLP experience\",\"authors\":\"Wai Lup Low, W. Tok, M. Lee, T. Ling\",\"doi\":\"10.1109/ICDE.2002.994723\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the increasing popularity of data-centric XML, data warehousing and mining applications are being developed for rapidly burgeoning XML data repositories. Data quality will no doubt be a critical factor for the success of such applications. Data cleaning, which refers to the processes used to improve data quality, has been well researched in the context of traditional databases. In earlier work we developed a knowledge-based framework for data cleaning relational databases. In this work, we present a novel attempt to apply this framework to XML databases. Our experimental dataset is the DBLP database, a popular online XML bibliography database used by many researchers.\",\"PeriodicalId\":191529,\"journal\":{\"name\":\"Proceedings 18th International Conference on Data Engineering\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-08-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings 18th International Conference on Data Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDE.2002.994723\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 18th International Conference on Data Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDE.2002.994723","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
With the increasing popularity of data-centric XML, data warehousing and mining applications are being developed for rapidly burgeoning XML data repositories. Data quality will no doubt be a critical factor for the success of such applications. Data cleaning, which refers to the processes used to improve data quality, has been well researched in the context of traditional databases. In earlier work we developed a knowledge-based framework for data cleaning relational databases. In this work, we present a novel attempt to apply this framework to XML databases. Our experimental dataset is the DBLP database, a popular online XML bibliography database used by many researchers.