Cargando…
Semantic relatedness and similarity of biomedical terms: examining the effects of recency, size, and section of biomedical publications on the performance of word2vec
BACKGROUND: Understanding semantic relatedness and similarity between biomedical terms has a great impact on a variety of applications such as biomedical information retrieval, information extraction, and recommender systems. The objective of this study is to examine word2vec’s ability in deriving s...
Autores principales: | Zhu, Yongjun, Yan, Erjia, Wang, Fei |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5496182/ https://www.ncbi.nlm.nih.gov/pubmed/28673289 http://dx.doi.org/10.1186/s12911-017-0498-1 |
Ejemplares similares
-
BioWordVec, improving biomedical word embeddings with subword information and MeSH
por: Zhang, Yijia, et al.
Publicado: (2019) -
Semantic Similarity in Biomedical Ontologies
por: Pesquita, Catia, et al.
Publicado: (2009) -
edge2vec: Representation learning using edge semantics for biomedical knowledge discovery
por: Gao, Zheng, et al.
Publicado: (2019) -
Calculating semantic relatedness for biomedical use in a knowledge-poor environment
por: Rybinski, Maciej, et al.
Publicado: (2014) -
Multi-domain semantic similarity in biomedical research
por: Ferreira, João D., et al.
Publicado: (2019)