Open AccessAutomatic Classification of Japanese Question Intention Based on Deep Learning
Author(s) -
Ling Jin,
Yancong Su,
Jianxun Li
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1757/1/012041
Subject(s) - artificial intelligence , computer science , word (group theory) , heuristic , feature (linguistics) , realization (probability) , deep learning , machine learning , natural language processing , segmentation , pattern recognition (psychology) , mathematics , linguistics , philosophy , statistics , geometry
In order to improve the effect of deep learning, this paper puts forward the method of deep learning of Japanese. Before classification, we need to preprocess the word segmentation and delete the termination word in the question, and then use the feature vector to represent it. By learning to store the information in the network, we use heuristic rules to classify the question intention, extract the feature vectors representing different types of questions, and then make statistical analysis on the corpus of actual marked questions, establish a classification system, and bind features based on word packets, Realization intention classification. The experimental results show that the classification accuracy and influence parameters are relatively higher after deep learning, and the automatic classification method of Japanese question intention should be unique.