Japanese Short Text Classification Based on CNN-BiLSTM-Attention

• Published in: Procedia computer science Vol. 262; pp. 320 - 329
• Main Authors: Chen, Tianyang, Xie, Zexian
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 2025
• Subjects: CNN-BiLSTM-Attention; Global Context Modeling; Japanese Short Text Classification; Local Feature Extraction; Self-Attention Mechanism; CNN-BiLSTM-Attention; Self-Attention Mechanism; Japanese Short Text Classification; Local Feature Extraction; Global Context Modeling

Due to the limited context information of the text, the traditional statistical feature-based method is difficult to effectively model the semantic relationship in the Japanese short text classification task, resulting in limited classification effect. To this end, this paper introduces the CNN-BiLS...