{"title":"PyExplore:没有查询日志的数据探索的查询建议","authors":"Apostolos Glenis, G. Koutrika","doi":"10.1145/3448016.3452762","DOIUrl":null,"url":null,"abstract":"Helping users explore data becomes increasingly more important as databases get larger and more complex. In this demo, we present PyExplore, a data exploration tool aimed at helping end users formulate queries over new datasets. PyExplore takes as input an initial query from the user along with some parameters and provides interesting queries by leveraging data correlations and diversity.","PeriodicalId":360379,"journal":{"name":"Proceedings of the 2021 International Conference on Management of Data","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"PyExplore: Query Recommendations for Data Exploration without Query Logs\",\"authors\":\"Apostolos Glenis, G. Koutrika\",\"doi\":\"10.1145/3448016.3452762\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Helping users explore data becomes increasingly more important as databases get larger and more complex. In this demo, we present PyExplore, a data exploration tool aimed at helping end users formulate queries over new datasets. PyExplore takes as input an initial query from the user along with some parameters and provides interesting queries by leveraging data correlations and diversity.\",\"PeriodicalId\":360379,\"journal\":{\"name\":\"Proceedings of the 2021 International Conference on Management of Data\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-06-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2021 International Conference on Management of Data\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3448016.3452762\",\"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 2021 International Conference on Management of Data","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3448016.3452762","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
PyExplore: Query Recommendations for Data Exploration without Query Logs
Helping users explore data becomes increasingly more important as databases get larger and more complex. In this demo, we present PyExplore, a data exploration tool aimed at helping end users formulate queries over new datasets. PyExplore takes as input an initial query from the user along with some parameters and provides interesting queries by leveraging data correlations and diversity.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
