PDF] Mining and Ranking Biomedical Synonym Candidates from
Por um escritor misterioso
Last updated 30 março 2025
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The results show that PRF-based reranking outperformed word embedding based approach and a strong baseline using interwiki link frequency, and suggests that medical synonyms mined from Wikipedia can increase the coverage of existing synonym resources such as UMLS. Biomedical synonyms are important resources for Natural Language Processing in Biomedical domain. Existing synonym resources (e.g., the UMLS) are not complete. Manual efforts for expanding and enriching these resources are prohibitively expensive. We therefore develop and evaluate approaches for automated synonym extraction from Wikipedia. Using the inter-wiki links, we extracted the candidate synonyms (anchor-text e.g., “increased thirst”) in a Wikipedia page and the title (e.g., “polyuria”) of its corresponding linked page. We rank synonym candidates with word embedding and pseudo-relevance feedback (PRF). Our results show that PRF-based reranking outperformed word embedding based approach and a strong baseline using interwiki link frequency. A hybrid method, Rank Score Combination, achieved the best results. Our analysis also suggests that medical synonyms mined from Wikipedia can increase the coverage of existing synonym resources such as UMLS.
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Are We There Yet? A Roadmap of Network Visualization from Surveys
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Integrating domain knowledge for biomedical text analysis into
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Constructing knowledge graphs and their biomedical applications
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Evaluating sentence representations for biomedical text: Methods
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PDF] Mining and Ranking Biomedical Synonym Candidates from
Chemical Evolution of Natural Product Structure
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Those Who Understand: Knowledge Growth in Teaching - LEE S
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PDF) Biomedical Natural Language Processing and Text Mining
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Predicting protein and pathway associations for understudied dark
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