{"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}
引用次数: 4
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.