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This discussion was conducted at a recent panel at the 28th International Conference on Database Systems for Advanced Applications (DASFAA 2023), held April 17-20, 2023 in Tianjin, China.
Scaling to very very large corpora for natural language disambiguation
Michele Banko and Eric Brill · 2001
Earlier work this paper cites.
Debugging schema mappings with routes
Laura Chiticariu and Wang Chiew Tan · 2006
Earlier work this paper cites.
Provenance in databases: Why, how, and where
James Cheney, Laura Chiticariu, and Wang Chiew Tan · 2009
Earlier work this paper cites.
Tuning database configuration parameters with ituned
Songyun Duan, Vamsidhar Thummala, and Shivnath Babu · 2009
Earlier work this paper cites.
Schema Matching and Mapping
Zohra Bellahsene, Angela Bonifati, and Erhard Rahm, editors · 2011
Earlier work this paper cites.
Probabilistic machine learning and artificial intelligence
Zoubin Ghahramani · 2015
Earlier work this paper cites.
Crowdsourced data management: A survey
Guoliang Li and Jiannan Wang and Yudian Zheng and Michael J. Franklin · 2016
Earlier work this paper cites.
A survey of general-purpose crowdsourcing techniques
Anand Inasu Chittilappilly and Lei Chen and Sihem Amer-Yahia · 2016
Earlier work this paper cites.
Interactive mapping specification with exemplar tuples
Angela Bonifati, Ugo Comignani, Emmanuel Coquery, and Romuald Thion · 2017
Earlier work this paper cites.
Automatic database management system tuning through large-scale machine learning
Dana Van Aken, Andrew Pavlo, Geoffrey J Gordon, and Bohan Zhang · 2017
Earlier work this paper cites.
User-guided repairing of inconsistent knowledge bases
Abdallah Arioua and Angela Bonifati · 2018
Earlier work this paper cites.
Querying Graphs
Angela Bonifati, George H. L. Fletcher, Hannes Voigt, and Nikolay Yakovets · 2018
Earlier work this paper cites.
Data integration: The current status and the way forward
Michael Stonebraker and Ihab F. Ilyas · 2018
Cited alongside, same era.
Chasing sets: How to use existential rules for expressive reasoning
David Carral, Irina Dragoste, Markus Krötzsch, and Christian Lewe · 2019
Cited alongside, same era.
Are we really making much progress? A worrying analysis of recent neural recommendation approaches
Maurizio Ferrari Dacrema, Paolo Cremonesi, and Dietmar Jannach · 2019
Cited alongside, same era.
An analytical study of large SPARQL query logs
Angela Bonifati, Wim Martens, and Thomas Timm · 2020
Cited alongside, same era.
Dual supervision framework for relation extraction with distant supervision and human annotation
Woohwan Jung and Kyuseok Shim · 2020
Cited alongside, same era.
Flexmatch: Boosting semi-supervised learning with curriculum pseudo labeling
Bowen Zhang, Yidong Wang, Wenxin Hou, HAO WU, Jindong Wang, Manabu Okumura, and Takahiro Shinozaki · 2021
Later among the works it cites.
Towards ai-powered data-driven education
Sihem Amer-Yahia · 2022
Later among the works it cites.
Probabilistic machine learning: An introduction
Kevin Patrick Murphy · 2022
Later among the works it cites.
ACM Policy on Authorship , 2023
ACM · 2023
Closest in time.
Auggpt: Leveraging chatgpt for text data augmentation, 2023
Haixing Dai, Zhengliang Liu, Wenxiong Liao, Xiaoke Huang, Yihan Cao, Zihao Wu, Lin Zhao, Shaochen Xu, Wei Liu, Ninghao Liu, Sheng Li, Dajiang Zhu, Hongmin Cai, Lichao Sun, Quanzheng Li, Dinggang Shen, Tianming Liu, and Xiang Li · 2023
Closest in time.
A guide to using ChatGPT for data science projects, 2023
DataCamp · 2023
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Chen Liang, Yue Yu, Haoming Jiang, Siawpeng Er, Ruijia Wang, Tuo Zhao, and Chao Zhang · 2020
Cited alongside, same era.
Exchanging data under policy views
Angela Bonifati, Ugo Comignani, and Efthymia Tsamoura · 2021
Cited alongside, same era.
How useful is meta-recommendation? an empirical investigation
Nassim Bouarour, Idir Benouaret, and Sihem Amer-Yahia · 2021
Cited alongside, same era.
The future is big graphs: a community view on graph processing systems
Sherif Sakr, Angela Bonifati, Hannes Voigt, Alexandru Iosup, Khaled Ammar, Renzo Angles, Walid G. Aref, Marcelo Arenas, Maciej Besta, Peter A. Boncz, Khuzaima Daudjee, Emanuele Della Valle, Stefania Dumbrava, Olaf Hartig, Bernhard Haslhofer, Tim Hegeman, Jan Hidders, Katja Hose, Adriana Iamnitchi, Vasiliki Kalavri, Hugo Kapp, Wim Martens, M. Tamer Özsu, Eric Peukert, Stefan Plantikow, Mohamed Ragab, Matei Ripeanu, Semih Salihoglu, Christian Schulz, Petra Selmer, Juan F. Sequeda, Joshua Shinavier, Gábor Szárnyas, Riccardo Tommasini, Antonino Tumeo, Alexandru Uta, Ana Lucia Varbanescu, Hsiang-Yun Wu, Nikolay Yakovets, Da Yan, and Eiko Yoneki · 2021
Cited alongside, same era.
Meta self-training for few-shot neural sequence labeling
Yaqing Wang, Subhabrata Mukherjee, Haoda Chu, Yuancheng Tu, Ming Wu, Jing Gao, and Ahmed Hassan Awadallah · 2021
Cited alongside, same era.
Knowledge graphs 2021: A data odyssey
Gerhard Weikum · 2021
Cited alongside, same era.
QA-GNN: reasoning with language models and knowledge graphs for question answering
Michihiro Yasunaga, Hongyu Ren, Antoine Bosselut, Percy Liang, and Jure Leskovec · 2021
Cited alongside, same era.
Learnings from data integration for augmented language models
Alon Y. Halevy and Jane Dwivedi-Yu · 2023
Closest in time.
Chatgpt in computer science education, 2023
Orit Hazzan · 2023
Closest in time.
Data management of ai-powered education technologies: Challenges and opportunities
Hassam Khosravi, Shazia Sadiq, and Sihem Amer-Yahia · 2023
Closest in time.
LangChain Chat, 2023
LangChain · 2023
Closest in time.
RESDSQL: Decoupling schema linking and skeleton parsing for text-to-SQL
Haoyang Li, Jing Zhang, Cuiping Li, and Hong Chen · 2023
Closest in time.
Hoping for the best as ai evolves
Gary Marcus · 2023
Closest in time.