Unsupervised String Transformation Learning for Entity Consolidation
暂无分享,去创建一个
Michael Stonebraker | Guoliang Li | Samuel Madden | Mourad Ouzzani | Ihab F. Ilyas | Nan Tang | Ziawasch Abedjan | Dong Deng | Wenbo Tao | Ahmed Elmagarmid | S. Madden | M. Stonebraker | I. Ilyas | A. Elmagarmid | M. Ouzzani | N. Tang | Dong Deng | Ziawasch Abedjan | Wenbo Tao | Guoliang Li
[1] Surajit Chaudhuri,et al. Learning String Transformations From Examples , 2009, Proc. VLDB Endow..
[2] Divesh Srivastava,et al. Less is More: Selecting Sources Wisely for Integration , 2012, Proc. VLDB Endow..
[3] Pedro M. Domingos,et al. Entity Resolution with Markov Logic , 2006, Sixth International Conference on Data Mining (ICDM'06).
[4] Raymond J. Mooney,et al. Adaptive duplicate detection using learnable string similarity measures , 2003, KDD '03.
[5] Ahmed K. Elmagarmid,et al. Duplicate Record Detection: A Survey , 2007, IEEE Transactions on Knowledge and Data Engineering.
[6] Tom M. Mitchell,et al. Generalization as Search , 2002 .
[7] Bo Zhao,et al. Resolving conflicts in heterogeneous data by truth discovery and source reliability estimation , 2014, SIGMOD Conference.
[8] Daniel Jurafsky,et al. Speech and language processing: an introduction to natural language processing, computational linguistics, and speech recognition, 2nd Edition , 2009, Prentice Hall series in artificial intelligence.
[9] Pushmeet Kohli,et al. RobustFill: Neural Program Learning under Noisy I/O , 2017, ICML.
[10] Jeffrey Xu Yu,et al. Entity Matching: How Similar Is Similar , 2011, Proc. VLDB Endow..
[11] Michael Stonebraker,et al. The Data Civilizer System , 2017, CIDR.
[12] Fernando De la Torre,et al. Facing Imbalanced Data--Recommendations for the Use of Performance Metrics , 2013, 2013 Humaine Association Conference on Affective Computing and Intelligent Interaction.
[13] Philip S. Yu,et al. Truth Discovery with Multiple Conflicting Information Providers on the Web , 2008, IEEE Trans. Knowl. Data Eng..
[14] AnHai Doan,et al. Falcon: Scaling Up Hands-Off Crowdsourced Entity Matching to Build Cloud Services , 2017, SIGMOD Conference.
[15] Wenfei Fan,et al. Determining the relative accuracy of attributes , 2013, SIGMOD '13.
[16] GulwaniSumit. Automating string processing in spreadsheets using input-output examples , 2011 .
[17] Felix Naumann,et al. Data Fusion – Resolving Data Conflicts for Integration , 2009 .
[18] Sumit Gulwani,et al. Automating string processing in spreadsheets using input-output examples , 2011, POPL '11.
[19] William W. Cohen,et al. Learning to match and cluster large high-dimensional data sets for data integration , 2002, KDD.
[20] Yeye He,et al. Transform-Data-by-Example (TDE): An Extensible Search Engine for Data Transformations , 2018, Proc. VLDB Endow..
[21] Michael Stonebraker,et al. Approximate String Joins with Abbreviations , 2017, Proc. VLDB Endow..
[22] Sumit Gulwani,et al. Neural-Guided Deductive Search for Real-Time Program Synthesis from Examples , 2018, ICLR.
[23] Jeffrey F. Naughton,et al. Corleone: hands-off crowdsourcing for entity matching , 2014, SIGMOD Conference.
[24] H. V. Jagadish,et al. Foofah: Transforming Data By Example , 2017, SIGMOD Conference.
[25] P. Ivax,et al. A THEORY FOR RECORD LINKAGE , 2004 .
[26] Pierre Baldi,et al. Assessing the accuracy of prediction algorithms for classification: an overview , 2000, Bioinform..
[27] Philip S. Yu,et al. Truth Discovery with Multiple Conflicting Information Providers on the Web , 2007, IEEE Transactions on Knowledge and Data Engineering.
[28] Michael Stonebraker,et al. DataXFormer: A robust transformation discovery system , 2016, 2016 IEEE 32nd International Conference on Data Engineering (ICDE).
[29] Christopher Ré,et al. SLiMFast: Guaranteed Results for Data Fusion and Source Reliability , 2015, SIGMOD Conference.
[30] AnHai Doan,et al. Technical Perspective:: Toward Building Entity Matching Management Systems , 2016, SGMD.
[31] Elena Console,et al. Data Fusion , 2009, Encyclopedia of Database Systems.
[32] Rishabh Singh,et al. BlinkFill: Semi-supervised Programming By Example for Syntactic String Transformations , 2016, Proc. VLDB Endow..
[33] Sumit Gulwani,et al. Learning Semantic String Transformations from Examples , 2012, Proc. VLDB Endow..
[34] Ziqi Wang,et al. A Probabilistic Approach to String Transformation , 2014, IEEE Transactions on Knowledge and Data Engineering.
[35] Laure Berti-Équille,et al. Truth Discovery Algorithms: An Experimental Evaluation , 2014, ArXiv.
[36] Michael Stonebraker,et al. Dataxformer: Leveraging the Web for Semantic Transformations , 2015, CIDR.
[37] Fred J. Damerau,et al. A technique for computer detection and correction of spelling errors , 1964, CACM.
[38] Divesh Srivastava,et al. Truth Discovery and Copying Detection in a Dynamic World , 2009, Proc. VLDB Endow..
[39] Wenfei Fan,et al. Inferring data currency and consistency for conflict resolution , 2013, 2013 IEEE 29th International Conference on Data Engineering (ICDE).
[40] AnHai Doan,et al. Magellan: Toward Building Entity Matching Management Systems over Data Science Stacks , 2016, Proc. VLDB Endow..
[41] Jennifer Widom,et al. Swoosh: a generic approach to entity resolution , 2008, The VLDB Journal.
[42] Sumit Gulwani,et al. Spreadsheet data manipulation using examples , 2012, CACM.
[43] Michael Stonebraker,et al. Data Curation at Scale: The Data Tamer System , 2013, CIDR.
[44] Jeffrey Heer,et al. Wrangler: interactive visual specification of data transformation scripts , 2011, CHI.
[45] Hector Garcia-Molina,et al. Incremental entity resolution on rules and data , 2014, The VLDB Journal.
[46] Hector Garcia-Molina,et al. Entity resolution with evolving rules , 2010, Proc. VLDB Endow..
[47] Armando Solar-Lezama,et al. The Sketching Approach to Program Synthesis , 2009, APLAS.