Subject identification of open-source information for defense science and technology frontiers
A feature fusion subject identification and classification model based on deep learning to address the imbalanced data classification problem affecting fine-grained subjects in the field of defense science and technology frontiers is proposed.Based on the semantic features extracted using the Sentence-BERT pre-trained model,the proposed model fuses the entity features extracted with the help of the named entity recognition technology and establishes tracking and monitoring capabilities for specific subjects in the field of defense science and technology frontiers.The experimental results show superior model performance.The model has been practically applied and has achieved noticeable results.
defense science and technology frontiersubject identificationfusion featuresemantic similaritynamed entity recognition
NETL
NSTL
万方数据
