Paper Title: "Evaluate the efficiency of a hybrid model based on Convolutional Neural Network and Long Short-Term Memory in Information Technology Job Graph Network"
Student Contributors:
Nguyen Minh Nhut – 17520867 –HTCL2017 – Co-author.
Dang Minh Quan – 19520867 – HTCL2019 – Co-author.
Le Mai Duy Khanh – 19521679 – HTCL 2019 – Co-author.
Supervising Teacher: Assoc. Prof. Dr. Nguyen Dinh Thuan
Paper Summary:
The advancement of technology has positively impacted society's lifestyle, providing more job opportunities. This may influence the career decisions of information technology students regarding their future professions. To help IT students in Vietnam and neighboring countries connect and interact with employers to find employment, we developed the ISCV application using Smart Contracts in Blockchain technology to facilitate connections and store information. We also utilized several machine learning algorithms, including Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), Bidirectional Long Short-Term Memory (BiLSTM), to create a proposed system that can assist individuals in choosing jobs that match their skills and capabilities. Furthermore, we proposed a hybrid model combining Convolutional Neural Network (CNN) with Long Short-Term Memory. The Hybrid CNN-LSTM model leverages the feature extraction capability of CNN from input data and the sequential learning ability of LSTM. Training and testing datasets were collected from job search websites. We used classification performance metrics, including Accuracy, Recall, Precision, and Micro-F1, to evaluate the models' performance. The final experimental results demonstrate that the Hybrid CNN-LSTM model has the highest accuracy.
"We would like to express our gratitude to Assoc. Prof. Dr. Nguyen Dinh Thuan – Dean of the Faculty of Information System for his dedicated guidance and for pointing out our limitations during the research and publication of this international scientific paper."
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Hai Bang - Communications Collaborator, University of Information Technology
English version: Phan Huy Hoang
