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Schema matching is a crucial task in data integration, involving the alignment of a source schema with a target schema to establish correspondence between their elements.
Relevance feedback in information retrieval
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COMA - A System for Flexible Combination of Schema Matching Approaches. In Very Large Data Bases Conference
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How to Fine-Tune BERT for Text Classification?. In China National Conference on Chinese Computational Linguistics
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Language Models are Few-Shot Learners
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, T. J. Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeff Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 2020
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Valentine: Evaluating Matching Techniques for Dataset Discovery
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SMAT: An Attention-Based Deep Learning Solution to the Automation of Schema Matching
Jing Zhang, Bonggun Shin, Jinho D. Choi, and Joyce Ho. 2021 · 2021
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New and improved embedding model
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Summary of ChatGPT-Related Research and Perspective Towards the Future of Large Language Models
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Deep entity matching with pre-trained language models
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ADnEV: Cross-Domain Schema Matching using Deep Similarity Matrix Adjustment and Evaluation
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Learning to Rerank Schema Matches
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Deep Learning Based Text Classification: A Comprehensive Review
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Transformation and Evaluation of the MIMIC Database in the OMOP Common Data Model: Development and Usability Study
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Learning to Characterize Matching Experts. In 2021 IEEE 37th International Conference on Data Engineering (ICDE) . 1236–1247
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Large Language Models as General Pattern Machines
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Large Language Models as Data Preprocessors
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Schema Matching using Pre-Trained Language Models
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