Jiewen Huang, Lyublena Antova, Christoph E. Koch, Dan Olteanu
{"title":"MayBMS:一个概率数据库管理系统","authors":"Jiewen Huang, Lyublena Antova, Christoph E. Koch, Dan Olteanu","doi":"10.1145/1559845.1559984","DOIUrl":null,"url":null,"abstract":"MayBMS is a state-of-the-art probabilistic database management system which leverages the strengths of previous database research for achieving scalability. As a proof of concept for its ease of use, we have built on top of MayBMS a Web-based application that offers NBA-related information based on what-if analysis of team dynamics using data available at www.nba.com.","PeriodicalId":344093,"journal":{"name":"Proceedings of the 2009 ACM SIGMOD International Conference on Management of data","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"166","resultStr":"{\"title\":\"MayBMS: a probabilistic database management system\",\"authors\":\"Jiewen Huang, Lyublena Antova, Christoph E. Koch, Dan Olteanu\",\"doi\":\"10.1145/1559845.1559984\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"MayBMS is a state-of-the-art probabilistic database management system which leverages the strengths of previous database research for achieving scalability. As a proof of concept for its ease of use, we have built on top of MayBMS a Web-based application that offers NBA-related information based on what-if analysis of team dynamics using data available at www.nba.com.\",\"PeriodicalId\":344093,\"journal\":{\"name\":\"Proceedings of the 2009 ACM SIGMOD International Conference on Management of data\",\"volume\":\"37 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-06-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"166\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2009 ACM SIGMOD International Conference on Management of data\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1559845.1559984\",\"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 of the 2009 ACM SIGMOD International Conference on Management of data","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1559845.1559984","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
MayBMS: a probabilistic database management system
MayBMS is a state-of-the-art probabilistic database management system which leverages the strengths of previous database research for achieving scalability. As a proof of concept for its ease of use, we have built on top of MayBMS a Web-based application that offers NBA-related information based on what-if analysis of team dynamics using data available at www.nba.com.