TY - GEN
T1 - Short Text Classification with A Convolutional Neural Networks Based Method
AU - Hu, Yibo
AU - Yi, Yang
AU - Yang, Tao
AU - Pan, Quan
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/12/18
Y1 - 2018/12/18
N2 - The traditional machine learning algorithms are easily affected by datasets in short text classification tasks, so they have weak generalization ability when confronted with new situations. This paper presents a new method SVMCNN by combining Convolutional Neural Networks and Support Vector Machine. Training the SVMCNN model with labeled datasets, and using the collected Twitter data for classification test. The results show that the SVMCNN, especially pre-trained SVMCNN has good performance in short text classification, which gets the high Precision rate, Recall rate and F1-measure.
AB - The traditional machine learning algorithms are easily affected by datasets in short text classification tasks, so they have weak generalization ability when confronted with new situations. This paper presents a new method SVMCNN by combining Convolutional Neural Networks and Support Vector Machine. Training the SVMCNN model with labeled datasets, and using the collected Twitter data for classification test. The results show that the SVMCNN, especially pre-trained SVMCNN has good performance in short text classification, which gets the high Precision rate, Recall rate and F1-measure.
UR - http://www.scopus.com/inward/record.url?scp=85060812401&partnerID=8YFLogxK
U2 - 10.1109/ICARCV.2018.8581332
DO - 10.1109/ICARCV.2018.8581332
M3 - 会议稿件
AN - SCOPUS:85060812401
T3 - 2018 15th International Conference on Control, Automation, Robotics and Vision, ICARCV 2018
SP - 1432
EP - 1435
BT - 2018 15th International Conference on Control, Automation, Robotics and Vision, ICARCV 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 15th International Conference on Control, Automation, Robotics and Vision, ICARCV 2018
Y2 - 18 November 2018 through 21 November 2018
ER -