PDF] Mining and Ranking Biomedical Synonym Candidates from

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.

Integrating domain knowledge for biomedical text analysis into

MAKE, Free Full-Text

Linking entities through an ontology using word embeddings and

Microorganisms, Free Full-Text

Predicting protein and pathway associations for understudied dark

Toxins, Free Full-Text

Biology, Free Full-Text

Sustainability, Free Full-Text

Identifying adverse childhood experiences with electronic health

PDF) Mining and Ranking Biomedical Synonym Candidates from Wikipedia

PDF] Mining and Ranking Biomedical Synonym Candidates from

PDF] Search with Synonyms: Problems and Solutions

Inverse Design of Materials That Exhibit the Magnetocaloric Effect

Statistical analysis of high-dimensional biomedical data: a gentle