Papers › Developing a Chatbot system using Deep Learning based for Universities consultancy
Developing a Chatbot system using Deep Learning based for Universities consultancy
Le-Tien Thuong, Nguyen-DP Tai, Huynh-Y Vy
Inspired by the recent successes of Deep Learning on Natural Language Processing (NLP), we propose a chatbot system using Deep Learning for Vietnamese Universities consultancy which can be implemented for any university. The system has three important tasks: User’s Intent Recognition, Dialogue Management, and Reply Channels. For the User’s Intent Recognition task, the Pattern Matching method is combined with the Text Classification model using Bidirectional-LSTM which has the Attention mechanism. Besides, we use the Deep Reinforcement Learning architecture to train an Agent for Dialogue Management task. In this paper, we conduct a Proof of Concept to the Ho Chi Minh City University of Technology (HCMUT). The experimental results achieve an average 89% F1-score of 3 classes of the Text Classification task using Deep Learning, the evaluation result of Dialogue Management that the rate of success achieves by 86%. Our demo version of a production web application is available at https://hcmutbot.herokuapp.com/.
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