DEEP LEARNING FOR SEMANTIC MATCHING: A SURVEY
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DOI:
https://doi.org/10.15625/1813-9663/37/4/16151Abstract
Semantic matching finds certain types of semantic relationships among schema/data constructs. Examples include entity matching, entity linking, coreference resolution, schema/ontology matching, semantic text similarity, textual entailment, question answering, tagging, etc. Semantic matching has received much attention in the database, AI, KDD, Web, and Semantic Web communities. Recently, many works have also applied deep learning (DL) to semantic matching. In this paper we survey this fast growing topic. We define the semantic matching problem, categorize its variations into a taxonomy, and describe important applications. We describe DL solutions for important variations of semantic matching. Finally, we discuss future R\&D directions.
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Published
12-10-2021
How to Cite
[1]
H. Li, Y. Govind, S. Mudgal, T. Rekatsinas, and A. Doan, “DEEP LEARNING FOR SEMANTIC MATCHING: A SURVEY”, JCC, vol. 37, no. 4, p. 365–402, Oct. 2021.
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