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Schema Matching using Machine Learning
lib:559074009c2bf360 (v1.0.0)
Authors: Tanvi Sahay,Ankita Mehta,Shruti Jadon
ArXiv: 1911.11543
Document: PDF DOI
Abstract URL: https://arxiv.org/abs/1911.11543v1
Schema Matching is a method of finding attributes that are either similar to each other linguistically or represent the same information. In this project, we take a hybrid approach at solving this problem by making use of both the provided data and the schema name to perform one to one schema matching and introduce the creation of a global dictionary to achieve one to many schema matching. We experiment with two methods of one to one matching and compare both based on their F-scores, precision, and recall. We also compare our method with the ones previously suggested and highlight differences between them.
ArXiv: 1911.11543
Document: PDF DOI
Abstract URL: https://arxiv.org/abs/1911.11543v1
Schema Matching is a method of finding attributes that are either similar to each other linguistically or represent the same information. In this project, we take a hybrid approach at solving this problem by making use of both the provided data and the schema name to perform one to one schema matching and introduce the creation of a global dictionary to achieve one to many schema matching. We experiment with two methods of one to one matching and compare both based on their F-scores, precision, and recall. We also compare our method with the ones previously suggested and highlight differences between them.
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