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Applying Convolutional Neural Network Model and Auto - expanded Corpus to Biomedical Abbreviation Disambiguation
2016
Journal of Engineering Science and Technology Review
The polysemy phenomenon of abbreviations in the medical domain generates a prodigious effect on the accuracy of computer auto text analysis. Hence, abbreviation disambiguation has been extensively studied in recent years. A large quantity of manually labelled corpuses is required in existing methods for training models, thereby restricting the application range of abbreviation disambiguation. This study proposes an abbreviation disambiguation method based on the convolutional neural network
doi:10.25103/jestr.096.27
fatcat:fhx7d4q265a3tk4jmxxuixh2aa