이청용 (Qinglong Li)
이청용 (Qinglong Li)
📌 Affiliation: Division of Computer Engineering (Big Data Track), Hansung University
📌 Position: Assistant Professor
📌 Office: Room 201, Research Building
📧 Email: leecy@hansung.ac.kr
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🎓 Education
Ph.D. in Engineering | Department of Big Data Analytics, Kyung Hee University (📅 Aug. 2024)
M.S. in Engineering | Department of Big Data Analytics, Kyung Hee University (📅 Feb. 2021)
B.B.A. | Department of Business Administration, Kyung Hee University (📅 Feb. 2019)
🏫 Academic Employment
Assistant Professor | Division of Computer Engineering, Hansung University (📅 Mar. 2025 – Present)
Research Professor | Department of Big Data Analytics, Kyung Hee University (📅 Sep. 2024 – Feb. 2025)
Lecturer | Department of Big Data Analytics, Kyung Hee University (📅 Mar. 2024 – Aug. 2024)
Senior Researcher | AI Business Research Center, Kyung Hee University (📅 Mar. 2019 – Feb. 2025)
🔬Research Areas
📊 Big Data Analytics | Machine learning-based big data analysis, development, and application of deep learning algorithms using multimodal and computer vision techniques
🎯 Personalized Services | Design and application of product and service recommender systems, development of personalized service algorithms based on deep learning and natural language processing
📝 Natural Language Processing | Development and application of online review filtering systems, development and optimization of text classification models based on large language models (LLMs)
📄 Research Papers (more than 50 papers)
Li, X., Li, Q., Ryu, D., & Kim, J. (2025). A BERT-based review helpfulness prediction model utilizing consistency of ratings and texts. Applied Intelligence, 55(6), 455.
Kim, D., Li, Q., Jang, D., & Kim, J. (2024). AXCF: Aspect‐based collaborative filtering for explainable recommendations. Expert Systems, 41(8), e13594.
Jang, D., Li, Q., Lee, C., & Kim, J. (2024). Attention-based multi-attribute matrix factorization for enhanced recommendation performance. Information Systems, 121, 102334.
Yang, S., Li, Q., Lim, H., & Kim, J. (2024). An attentive aspect-based recommendation model with deep neural network. IEEE Access, 12, 5781-5791.
Park, J., Li, X., Li, Q., & Kim, J. (2023). Impact on recommendation performance of online review helpfulness and consistency. Data Technologies and Applications, 57(2), 199-221.
Li, X., Li, Q., & Kim, J. (2023). A review helpfulness modeling mechanism for online e-commerce: Multi-channel CNN end‑to‑end approach. Applied Artificial Intelligence, 37(1), 2166226.
📌 For the full list of publications, please visit the Publications page.
🏆 Honors and Awards
🥇 Best Paper Award | Korean Intelligent Information Systems Society (KIISS) Spring Conference (2025) | Multimodal Transformer-Based AI Model for predicting Review Helpfulness with Review-Product Relevance
🥇 Best Paper Award | Korean Intelligent Information Systems Society (KIISS) Fall Conference (2024) | Leveraging AI-Driven Advanced Transformer for Summarized Review-Aware Recommendation
🏅 Outstanding Paper | Emerald Literati Awards (2024) | Impact on Recommendation Performance of Online Review Helpfulness and Consistency
🥈 Excellent Paper Award | Korean Operations Research and Management Science Society (KORMS) Fall Conference (2023) | A Cross-Domain Recommendation Model with Doc2Vec for Solving Data Sparsity Problems
🥈 Excellent Paper Award | Korean Operations Research and Management Science Society (KORMS) Fall Conference (2023) | A Personalized Restaurant Recommendation Model Exploiting Granular Customer Preferences
🥇 Best Paper Award | Korean IT Service Society (KITSS) Spring Conference (2023) | Development of a Graph Convolutional Network-Based Recommendation System Utilizing Explicit and Implicit Feedback
🥈 Excellent Paper Award | Korean Intelligent Information Systems Society (KIISS) Spring Conference (2021) | Enhancing Personalized Recommendation Service Performance through CNN-Based Prediction of Review Helpfulness Scores
📚 Lectures
Big Data Programming | Spring 2025, Hansung University
Data Mining | Spring 2025, Hansung University
Recommender Systems | Fall 2024, Kyung Hee University
Data Mining Theory and Practice | Fall 2024, Kyung Hee University (Graduate Course)
Big Data Decision Analysis | Spring 2024, Kyung Hee University
📑 Project Experience
Education and Research Group of Big Data Leaders for Sustainable Growth (BK21 Project) | NRF (📅 Sep. 1, 2024 – Feb. 28, 2025), Researcher / Research Professor
Development of a Consulting Framework Integrating Structured and Unstructured Data to Support the Sustainable Growth of Technology-Based Companies | KEIT (📅 May 1, 2020 – Dec. 31, 2022), Researcher
Development of a Business Model for AI-Based Personalized Job Search Support Service Using Big Data on Employment Information | KEIT (📅 Aug. 1, 2019 – Jan. 31, 2020), Researcher
Research on a Recommendation System Using Recurrent Neural Networks in IoT-Based Exhibition Environments | Kyung Hee University (📅 Mar. 1, 2019 – Feb. 23, 2020), Researcher
🔖 Patents
System and Method of Recommending Customized Course Subjects Based on Deep Learning | Patent No: 10-2021-0063216, South Korea, Granted
Consulting System for Supporting Decision-Making of Enterprises and Method Thereof | Patent Application No: 10-2022-0136712, South Korea, Pending
System and Method of Automatically Providing a Summary for Enterprise Consulting Information | Patent Application No: 10-2022-0136712, South Korea, Pending
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