{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T22:23:27Z","timestamp":1672611807080},"reference-count":9,"publisher":"Association for Computing Machinery (ACM)","issue":"12","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2015,8]]},"abstract":"<jats:p>\n            Data analysts often engage in data exploration tasks to discover interesting data patterns, without knowing exactly what they are looking for. Such exploration tasks can be very labor-intensive because they often require the user to review many results of ad-hoc queries and adjust the predicates of subsequent queries to balance the tradeoff between collecting all interesting information and reducing the size of returned data. In this demonstration we introduce\n            <jats:italic>AIDE<\/jats:italic>\n            , a system that automates these exploration tasks. AIDE steers the user towards interesting data areas based on her relevance feedback on database samples, aiming to achieve the goal of identifying all database objects that match the user interest with high efficiency. In our demonstration, conference attendees will see AIDE in action for a variety of exploration tasks on real-world datasets.\n          <\/jats:p>","DOI":"10.14778\/2824032.2824112","type":"journal-article","created":{"date-parts":[[2015,9,16]],"date-time":"2015-09-16T12:18:17Z","timestamp":1442405897000},"page":"1964-1967","source":"Crossref","is-referenced-by-count":4,"title":["AIDE"],"prefix":"10.14778","volume":"8","author":[{"given":"Yanlei","family":"Diao","sequence":"first","affiliation":[{"name":"UMass Amherst"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kyriaki","family":"Dimitriadou","sequence":"additional","affiliation":[{"name":"Brandeis University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhan","family":"Li","sequence":"additional","affiliation":[{"name":"Brandeis University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenzhao","family":"Liu","sequence":"additional","affiliation":[{"name":"UMass Amherst"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Olga","family":"Papaemmanouil","sequence":"additional","affiliation":[{"name":"Brandeis University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kemi","family":"Peng","sequence":"additional","affiliation":[{"name":"Brandeis University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liping","family":"Peng","sequence":"additional","affiliation":[{"name":"UMass Amherst"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2015,8]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"AuctionMark Benchmark http:\/\/hstore.cs.brown.edu\/projects\/auctionmark\/.  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In SIGMOD, 1990. 10.1145\/93605.98741"},{"key":"e_1_2_1_6_1","first-page":"1579","article-title":"Fast kernel classifiers with online and active learning","volume":"6","author":"Bordes A.","year":"2005","unstructured":"A. Bordes , S. Ertekin , Fast kernel classifiers with online and active learning . J. Mach. Learn. Res. , 6 : 1579 -- 1619 , Dec. 2005 . A. Bordes, S. Ertekin, et al. Fast kernel classifiers with online and active learning. J. Mach. Learn. Res., 6:1579--1619, Dec. 2005.","journal-title":"J. Mach. Learn. Res."},{"key":"e_1_2_1_7_1","volume-title":"Classification and Regression Trees","author":"Breiman L.","year":"1984","unstructured":"L. Breiman , J. H. Friedman , Classification and Regression Trees . Chapman and Hall\/CRC , 1984 . L. Breiman, J. H. Friedman, et al. Classification and Regression Trees. Chapman and Hall\/CRC, 1984."},{"key":"e_1_2_1_8_1","volume-title":"SIGMOD","author":"Dimitriadou K.","year":"2014","unstructured":"K. Dimitriadou , O. Papaemmanouil , and Y. Diao . Explore-by-Example: An Automatic Query Steering Framework for Interactive Data Exploration . In SIGMOD , 2014 . 10.1145\/2588555.2610523 K. Dimitriadou, O. Papaemmanouil, and Y. Diao. Explore-by-Example: An Automatic Query Steering Framework for Interactive Data Exploration. In SIGMOD, 2014. 10.1145\/2588555.2610523"},{"key":"e_1_2_1_9_1","volume-title":"SIGMOD","author":"Zhang T.","year":"1996","unstructured":"T. Zhang , R. Ramakrishnan , and M. Livny . BIRCH: An Efficient Data Clustering Method for Very Large Databases . In SIGMOD , 1996 . 10.1145\/235968.233324 T. Zhang, R. Ramakrishnan, and M. Livny. BIRCH: An Efficient Data Clustering Method for Very Large Databases. In SIGMOD, 1996. 10.1145\/235968.233324"}],"container-title":["Proceedings of the VLDB Endowment"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.14778\/2824032.2824112","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T10:08:18Z","timestamp":1672222098000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.14778\/2824032.2824112"}},"subtitle":["an automatic user navigation system for interactive data exploration"],"short-title":[],"issued":{"date-parts":[[2015,8]]},"references-count":9,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2015,8]]}},"alternative-id":["10.14778\/2824032.2824112"],"URL":"https:\/\/doi.org\/10.14778\/2824032.2824112","relation":{},"ISSN":["2150-8097"],"issn-type":[{"value":"2150-8097","type":"print"}],"subject":[],"published":{"date-parts":[[2015,8]]}}}