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Within enterprises, there is a growing need to intelligently navigate data lakes, specifically focusing on data discovery.
A survey of approaches to automatic schema matching
E. Rahm and P. A. Bernstein · 2001
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Webtables: exploring the power of tables on the web
M. J. Cafarella, A. Y. Halevy, D. Z. Wang, E. Wu, and Y. Zhang · 2008
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Finding related tables
A. D. Sarma, L. Fang, N. Gupta, A. Y. Halevy, H. Lee, F. Wu, R. Xin, and C. Yu · 2012
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Wikidata: A free collaborative knowledgebase
D. Vrandecic and M. Krötzsch · 2014
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Wikidata: A free collaborative knowledgebase
D. Vrandečić and M. Krötzsch · 2014
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Magellan: Toward building entity matching management systems
P. Konda, S. Das, P. S. G. C., A. Doan, A. Ardalan, J. R. Ballard, H. Li, F. Panahi, H. Zhang, J. F. Naughton, S. Prasad, G. Krishnan, R. Deep, and V. Raghavendra · 2016
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A large public corpus of web tables containing time and context metadata
O. Lehmberg, D. Ritze, R. Meusel, and C. Bizer · 2016
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Deep learning for entity matching: A design space exploration
S. Mudgal, H. Li, T. Rekatsinas, A. Doan, Y. Park, G. Krishnan, R. Deep, E. Arcaute, and V. Raghavendra · 2018
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Table union search on open data
F. Nargesian, E. Zhu, K. Q. Pu, and R. J. Miller · 2018
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Spider: A large-scale human-labeled dataset for complex and cross-domain semantic parsing and text-to-SQL task
T. Yu, R. Zhang, K. Yang, M. Yasunaga, D. Wang, Z. Li, J. Ma, I. Li, Q. Yao, S. Roman, Z. Zhang, and D. Radev · 2018
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BERT: pre-training of deep bidirectional transformers for language understanding
J. Devlin, M. Chang, K. Lee, and K. Toutanova · 2019
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Viznet: Towards A large-scale visualization learning and benchmarking repository
K. Z. Hu, S. N. S. Gaikwad, M. Hulsebos, M. A. Bakker, E. Zgraggen, C. A. Hidalgo, T. Kraska, G. Li, A. Satyanarayan, and Ç. Demiralp · 2019
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Sherlock: A deep learning approach to semantic data type detection
M. Hulsebos, K. Z. Hu, M. A. Bakker, E. Zgraggen, A. Satyanarayan, T. Kraska, Ç. Demiralp, and C. A. Hidalgo · 2019
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Data lake management: Challenges and opportunities
F. Nargesian, E. Zhu, R. J. Miller, K. Q. Pu, and P. C. Arocena · 2019
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JOSIE: overlap set similarity search for finding joinable tables in data lakes
E. Zhu, D. Deng, F. Nargesian, and R. J. Miller · 2019
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Electra: Pre-training text encoders as discriminators rather than generators
K. Clark, M.-T. Luong, Q. V. Le, and C. D. Manning · 2020
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TURL: table understanding through representation learning
X. Deng, H. Sun, A. Lees, Y. Wu, and C. Yu · 2020
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Tapas: Weakly supervised table parsing via pre-training
J. Herzig, P. K. Nowak, T. Müller, F. Piccinno, and J. M. Eisenschlos · 2020
Valentine: Evaluating matching techniques for dataset discovery
C. Koutras, G. Siachamis, A. Ionescu, K. Psarakis, J. Brons, M. Fragkoulis, C. Lofi, A. Bonifati, and A. Katsifodimos · 2021
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Retrieving complex tables with multi-granular graph representation learning
F. Wang, K. Sun, M. Chen, J. Pujara, and P. A. Szekely · 2021
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TUTA: tree-based transformers for generally structured table pre-training
Z. Wang, H. Dong, R. Jia, J. Li, Z. Fu, S. Han, and D. Zhang · 2021
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Grappa: Grammar-augmented pre-training for table semantic parsing
T. Yu, C. Wu, X. V. Lin, B. Wang, Y. C. Tan, X. Yang, D. R. Radev, R. Socher, and C. Xiong · 2021
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Integrating data lake tables
A. Khatiwada, R. Shraga, W. Gatterbauer, and R. J. Miller · 2022
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TAPEX: table pre-training via learning a neural SQL executor
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Deep entity matching with pre-trained language models
Y. Li, J. Li, Y. Suhara, A. Doan, and W. Tan · 2020
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Tabert: Pretraining for joint understanding of textual and tabular data
P. Yin, G. Neubig, W. Yih, and S. Riedel · 2020
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Sato: Contextual semantic type detection in tables
D. Zhang, Y. Suhara, J. Li, M. Hulsebos, Ç. Demiralp, and W. Tan · 2020
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Web table extraction, retrieval, and augmentation: A survey
S. Zhang and K. Balog · 2020
Cited alongside, same era.
Global table extractor (gte): A framework for joint table identification and cell structure recognition using visual context, 2020
X. Zheng, D. Burdick, L. Popa, X. Zhong, and N. X. R. Wang · 2020
Cited alongside, same era.
TABBIE: pretrained representations of tabular data
H. Iida, D. Thai, V. Manjunatha, and M. Iyyer · 2021
Cited alongside, same era.
Q. Liu, B. Chen, J. Guo, M. Ziyadi, Z. Lin, W. Chen, and J. Lou · 2022
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Annotating columns with pre-trained language models
Y. Suhara, J. Li, Y. Li, D. Zhang, Ç. Demiralp, C. Chen, and W. Tan · 2022
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Transformers for Tabular Data Representation: A Survey of Models and Applications
G. Badaro, M. Saeed, and P. Papotti · 2023
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Proceedings of the Semantic Web Challenge on Tabular Data to Knowledge Graph Matching, SemTab 2021, co-located with the 21st International Semantic Web Conference, ISWC 2022, Virtual conference, October 23-27, 2022 , volume 3320 of CEUR Workshop Proceedings , 2023. CEUR-WS.org
V. Efthymiou, E. Jiménez-Ruiz, J. Chen, V. Cutrona, O. Hassanzadeh, J. Sequeda, K. Srinivas, N. Abdelmageed, and M. Hulsebos, editors · 2023
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Data lakes: A survey of functions and systems
R. Hai, C. Koutras, C. Quix, and M. Jarke · 2023
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Santos: Relationship-based semantic table union search
A. Khatiwada, G. Fan, R. Shraga, Z. Chen, W. Gatterbauer, R. J. Miller, and M. Riedewald · 2023
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