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Quality of word and concept embeddings in targetted biomedical domains
Embeddings are fundamental resources often reused for building intelligent systems in the biomedical context. As a result, evaluating the quality of previously trained embeddings and ensuring they cover the desired information is critical for the success of applications. This paper proposes a new ev...
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Published in: | Heliyon 2023-06, Vol.9 (6), p.e16818-e16818, Article e16818 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites |
Online Access: | Get full text |
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Summary: | Embeddings are fundamental resources often reused for building intelligent systems in the biomedical context. As a result, evaluating the quality of previously trained embeddings and ensuring they cover the desired information is critical for the success of applications. This paper proposes a new evaluation methodology to test the coverage of embeddings against a targetted domain of interest. It defines measures to assess the terminology, similarity, and analogy coverage, which are core aspects of the embeddings. Then, it discusses the experimentation carried out on existing biomedical embeddings in the specific context of pulmonary diseases. The proposed methodology and measures are general and may be applied to any application domain. |
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ISSN: | 2405-8440 2405-8440 |
DOI: | 10.1016/j.heliyon.2023.e16818 |