{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:22:03Z","timestamp":1750220523376,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":24,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,1,2]],"date-time":"2021-01-02T00:00:00Z","timestamp":1609545600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,1,2]]},"DOI":"10.1145\/3430984.3431032","type":"proceedings-article","created":{"date-parts":[[2020,12,28]],"date-time":"2020-12-28T05:34:44Z","timestamp":1609133684000},"page":"213-217","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Scalable Database Normalization Powered by the Crowd"],"prefix":"10.1145","author":[{"given":"GSS Aditya","family":"Sairam","sequence":"first","affiliation":[{"name":"Indian Statistical Institute Kolkata, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Parasuram","family":"Kolli","sequence":"additional","affiliation":[{"name":"Indian Statistical Institute Kolkata, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anudeep","family":"Immidisetty","sequence":"additional","affiliation":[{"name":"Indian Statistical Institute Kolkata, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pranav","family":"Kumar","sequence":"additional","affiliation":[{"name":"Indian Statistical Institute Kolkata, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Madhu","family":"Sudhan B","sequence":"additional","affiliation":[{"name":"Indian Statistical Institute Kolkata, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Malay","family":"Bhattacharyya","sequence":"additional","affiliation":[{"name":"Indian Statistical Institute Kolkata, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2021,1,2]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"DFD:Efficient Discovery of Functional Dependencies. CIKM 2014 - Proceedings of the 2014 ACM International Conference on Information and Knowledge Management (10 2014","author":"Abedjan Z.","year":"1829","unstructured":"Z. Abedjan , P. Schulze , and F. Naumann . 2014 . DFD:Efficient Discovery of Functional Dependencies. CIKM 2014 - Proceedings of the 2014 ACM International Conference on Information and Knowledge Management (10 2014 ). https:\/\/doi.org\/10.1145\/266 1829 .2661884 10.1145\/2661829.2661884 Z. Abedjan, P. Schulze, and F. Naumann. 2014. DFD:Efficient Discovery of Functional Dependencies. CIKM 2014 - Proceedings of the 2014 ACM International Conference on Information and Knowledge Management (10 2014). https:\/\/doi.org\/10.1145\/2661829.2661884"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.1973.10482434"},{"key":"e_1_3_2_1_3_1","unstructured":"P. Flach and I. Savnik. 1999. Database Dependency Discovery: A Machine Learning Approach. AI Commun 12 (02 1999).  P. Flach and I. Savnik. 1999. Database Dependency Discovery: A Machine Learning Approach. AI Commun 12 (02 1999)."},{"key":"e_1_3_2_1_4_1","unstructured":"P. Flach and I. Savnik. 1999. Database Dependency Discovery: A Machine Learning Approach. AI Commun 12 (02 1999).  P. Flach and I. Savnik. 1999. Database Dependency Discovery: A Machine Learning Approach. AI Commun 12 (02 1999)."},{"key":"#cr-split#-e_1_3_2_1_5_1.1","doi-asserted-by":"crossref","unstructured":"B. Flury and H. Riedwyl. 1981. Graphical Representation of Multivariate Data by Means of Asymmetrical Faces. Journal of The American Statistical Association - J AMER STATIST ASSN 76 (12 1981) 757-765. https:\/\/doi.org\/10.1080\/01621459.1981.10477718 10.1080\/01621459.1981.10477718","DOI":"10.1080\/01621459.1981.10477718"},{"key":"#cr-split#-e_1_3_2_1_5_1.2","doi-asserted-by":"crossref","unstructured":"B. Flury and H. Riedwyl. 1981. Graphical Representation of Multivariate Data by Means of Asymmetrical Faces. Journal of The American Statistical Association - J AMER STATIST ASSN 76 (12 1981) 757-765. https:\/\/doi.org\/10.1080\/01621459.1981.10477718","DOI":"10.1080\/01621459.1981.10477718"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/1989323.1989331"},{"key":"e_1_3_2_1_7_1","volume-title":"Tane: An Efficient Algorithm for Discovering Functional and Approximate Dependencies. Comput. J. 42 (02","author":"Huhtala Y.","year":"1999","unstructured":"Y. Huhtala . 1999 . Tane: An Efficient Algorithm for Discovering Functional and Approximate Dependencies. Comput. J. 42 (02 1999), 100\u2013111. https:\/\/doi.org\/10.1093\/comjnl\/42.2.100 10.1093\/comjnl Y. Huhtala. 1999. Tane: An Efficient Algorithm for Discovering Functional and Approximate Dependencies. Comput. J. 42 (02 1999), 100\u2013111. https:\/\/doi.org\/10.1093\/comjnl\/42.2.100"},{"key":"#cr-split#-e_1_3_2_1_8_1.1","doi-asserted-by":"crossref","unstructured":"S. Lopes J.-M. Petit and L. Lakhal. 2000. Efficient Discovery of Functional Dependencies and Armstrong Relations. 1777 (03 2000) 350-364. https:\/\/doi.org\/10.1007\/3-540-46439-5_24 10.1007\/3-540-46439-5_24","DOI":"10.1007\/3-540-46439-5_24"},{"key":"#cr-split#-e_1_3_2_1_8_1.2","doi-asserted-by":"crossref","unstructured":"S. Lopes J.-M. Petit and L. Lakhal. 2000. Efficient Discovery of Functional Dependencies and Armstrong Relations. 1777 (03 2000) 350-364. https:\/\/doi.org\/10.1007\/3-540-46439-5_24","DOI":"10.1007\/3-540-46439-5_24"},{"key":"#cr-split#-e_1_3_2_1_9_1.1","doi-asserted-by":"crossref","unstructured":"A. Marcus and A. Parameswaran. 2015. Crowdsourced Data Management: Industry and Academic Perspectives. Foundations and Trends in Databases 6 (01 2015) 1-161. https:\/\/doi.org\/10.1561\/1900000044 10.1561\/1900000044","DOI":"10.1561\/1900000044"},{"key":"#cr-split#-e_1_3_2_1_9_1.2","doi-asserted-by":"crossref","unstructured":"A. Marcus and A. Parameswaran. 2015. Crowdsourced Data Management: Industry and Academic Perspectives. Foundations and Trends in Databases 6 (01 2015) 1-161. https:\/\/doi.org\/10.1561\/1900000044","DOI":"10.1561\/1900000044"},{"key":"e_1_3_2_1_10_1","volume-title":"Proceedings of SPIE - The International Society for Optical Engineering (02","author":"Morris C.","year":"2000","unstructured":"C. Morris and D. Ebert . 2000. An Experimental Analysis of the Effectiveness of Features in Chernoff Faces . Proceedings of SPIE - The International Society for Optical Engineering (02 2000 ). https:\/\/doi.org\/10.1117\/12.384865 10.1117\/12.384865 C. Morris and D. Ebert. 2000. An Experimental Analysis of the Effectiveness of Features in Chernoff Faces. Proceedings of SPIE - The International Society for Optical Engineering (02 2000). https:\/\/doi.org\/10.1117\/12.384865"},{"key":"e_1_3_2_1_11_1","volume-title":"FUN: An Efficient Algorithm for Mining Functional and Embedded Dependencies. 1973 (01","author":"Novelli N.","year":"2008","unstructured":"N. Novelli and R. Cicchetti . 2008 . FUN: An Efficient Algorithm for Mining Functional and Embedded Dependencies. 1973 (01 2008), 189\u2013203. https:\/\/doi.org\/10.1007\/3-540-44503-X_13 10.1007\/3-540-44503-X_13 N. Novelli and R. Cicchetti. 2008. FUN: An Efficient Algorithm for Mining Functional and Embedded Dependencies. 1973 (01 2008), 189\u2013203. https:\/\/doi.org\/10.1007\/3-540-44503-X_13"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.14778\/2794367.2794377"},{"key":"#cr-split#-e_1_3_2_1_13_1.1","doi-asserted-by":"crossref","unstructured":"L. Pinto and C. Santos\u00a0Jr. 2018. Motivations of crowdsourcing contributors. Innovation & Management Review 15 (04 2018). https:\/\/doi.org\/10.1108\/INMR-02-2018-004 10.1108\/INMR-02-2018-004","DOI":"10.1108\/INMR-02-2018-004"},{"key":"#cr-split#-e_1_3_2_1_13_1.2","doi-asserted-by":"crossref","unstructured":"L. Pinto and C. Santos\u00a0Jr. 2018. Motivations of crowdsourcing contributors. Innovation & Management Review 15 (04 2018). https:\/\/doi.org\/10.1108\/INMR-02-2018-004","DOI":"10.1108\/INMR-02-2018-004"},{"key":"e_1_3_2_1_14_1","volume-title":"Mathematical, physical, and engineering sciences 371 (03","author":"von Ahn L.","year":"2013","unstructured":"L. von Ahn . 2013. Augmented intelligence: The Web and human intelligence. Philosophical transactions. Series A , Mathematical, physical, and engineering sciences 371 (03 2013 ), 20120383. https:\/\/doi.org\/10.1098\/rsta.2012.0383 10.1098\/rsta.2012.0383 L. von Ahn. 2013. Augmented intelligence: The Web and human intelligence. Philosophical transactions. Series A, Mathematical, physical, and engineering sciences 371 (03 2013), 20120383. https:\/\/doi.org\/10.1098\/rsta.2012.0383"},{"key":"#cr-split#-e_1_3_2_1_15_1.1","doi-asserted-by":"crossref","unstructured":"S. Wu X. Wang Z. Zhang and A. Tung. 2014. K-Anonymity for Crowdsourcing Database. Knowledge and Data Engineering IEEE Transactions on 26 (09 2014) 2207-2221. https:\/\/doi.org\/10.1109\/TKDE.2013.93 10.1109\/TKDE.2013.93","DOI":"10.1109\/TKDE.2013.93"},{"key":"#cr-split#-e_1_3_2_1_15_1.2","doi-asserted-by":"crossref","unstructured":"S. Wu X. Wang Z. Zhang and A. Tung. 2014. K-Anonymity for Crowdsourcing Database. Knowledge and Data Engineering IEEE Transactions on 26 (09 2014) 2207-2221. https:\/\/doi.org\/10.1109\/TKDE.2013.93","DOI":"10.1109\/TKDE.2013.93"},{"key":"#cr-split#-e_1_3_2_1_16_1.1","doi-asserted-by":"crossref","unstructured":"C. Wyss C. Giannella and E. Robertson. 2001. FastFDs: A Heuristic-Driven Depth-First Algorithm for Mining Functional Dependencies from Relation Instances Extended Abstract. (01 2001) 101-110. https:\/\/doi.org\/10.1007\/3-540-44801-2_11 10.1007\/3-540-44801-2_11","DOI":"10.1007\/3-540-44801-2_11"},{"key":"#cr-split#-e_1_3_2_1_16_1.2","doi-asserted-by":"crossref","unstructured":"C. Wyss C. Giannella and E. Robertson. 2001. FastFDs: A Heuristic-Driven Depth-First Algorithm for Mining Functional Dependencies from Relation Instances Extended Abstract. (01 2001) 101-110. https:\/\/doi.org\/10.1007\/3-540-44801-2_11","DOI":"10.1007\/3-540-44801-2_11"},{"key":"#cr-split#-e_1_3_2_1_17_1.1","doi-asserted-by":"crossref","unstructured":"H. Yao H. Hamilton and C. Butz. 2002. FD_Mine: Discovering Functional Dependencies in a Database Using Equivalences. (01 2002) 729-732. https:\/\/doi.org\/10.1109\/ICDM.2002.1184040 10.1109\/ICDM.2002.1184040","DOI":"10.1109\/ICDM.2002.1184040"},{"key":"#cr-split#-e_1_3_2_1_17_1.2","doi-asserted-by":"crossref","unstructured":"H. Yao H. Hamilton and C. Butz. 2002. FD_Mine: Discovering Functional Dependencies in a Database Using Equivalences. (01 2002) 729-732. https:\/\/doi.org\/10.1109\/ICDM.2002.1184040","DOI":"10.1109\/ICDM.2002.1184040"}],"event":{"name":"CODS COMAD 2021: 8th ACM IKDD CODS and 26th COMAD","acronym":"CODS COMAD 2021","location":"Bangalore India"},"container-title":["Proceedings of the 3rd ACM India Joint International Conference on Data Science &amp; Management of Data (8th ACM IKDD CODS &amp; 26th COMAD)"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3430984.3431032","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3430984.3431032","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T21:24:44Z","timestamp":1750195484000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3430984.3431032"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,1,2]]},"references-count":24,"alternative-id":["10.1145\/3430984.3431032","10.1145\/3430984"],"URL":"https:\/\/doi.org\/10.1145\/3430984.3431032","relation":{},"subject":[],"published":{"date-parts":[[2021,1,2]]},"assertion":[{"value":"2021-01-02","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}