Cargando…
An Efficient Parallelized Ontology Network-Based Semantic Similarity Measure for Big Biomedical Document Clustering
Semantic mining is always a challenge for big biomedical text data. Ontology has been widely proved and used to extract semantic information. However, the process of ontology-based semantic similarity calculation is so complex that it cannot measure the similarity for big text data. To solve this pr...
Autores principales: | Li, Meijing, Chen, Tianjie, Ryu, Keun Ho, Jin, Cheng Hao |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8594978/ https://www.ncbi.nlm.nih.gov/pubmed/34795792 http://dx.doi.org/10.1155/2021/7937573 |
Ejemplares similares
-
An Ensemble Semantic Textual Similarity Measure Based on Multiple Evidences for Biomedical Documents
por: Li, Meijing, et al.
Publicado: (2022) -
Semantic Similarity in Biomedical Ontologies
por: Pesquita, Catia, et al.
Publicado: (2009) -
From Ontology to Semantic Similarity: Calculation of Ontology-Based Semantic Similarity
por: Gan, Mingxin, et al.
Publicado: (2013) -
Discovering Thematically Coherent Biomedical Documents Using Contextualized Bidirectional Encoder Representations from Transformers-Based Clustering
por: Davagdorj, Khishigsuren, et al.
Publicado: (2022) -
Semantic similarity and machine learning with ontologies
por: Kulmanov, Maxat, et al.
Publicado: (2020)