Chinese User Service Intention Classification Based on Hybrid Neural Network
September 25, 2018 Β· Declared Dead Β· π Journal of Physics: Conference Series
"No code URL or promise found in abstract"
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Authors
Shengbin Jia, Yang Xiang
arXiv ID
1809.09408
Category
cs.AI: Artificial Intelligence
Cross-listed
cs.CL
Citations
2
Venue
Journal of Physics: Conference Series
Last Checked
4 months ago
Abstract
In order to satisfy the consumers' increasing personalized service demand, the Intelligent service has arisen. User service intention recognition is an important challenge for intelligent service system to provide precise service. It is difficult for the intelligent system to understand the semantics of user demand which leads to poor recognition effect, because of the noise in user requirement descriptions. Therefore, a hybrid neural network classification model based on BiLSTM and CNN is proposed to recognize users service intentions. The model can fuse the temporal semantics and spatial semantics of the user descriptions. The experimental results show that our model achieves a better effect compared with other models, reaching 0.94 on the F1 score.
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