👋 Hi, I'm Qinglong Li (이청용)

Assistant Professor at Hansung University specializing in Big Data Analytics, Recommender Systems, and Natural Language Processing. I develop intelligent algorithms for data-driven decision-making and personalized services.

• 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)

• 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.

A total of more than 50 papers have been published to date. For the full list, please refer to my Google Scholar.

• Best Paper Award, KIISS Spring Conference (2025)
  Multimodal Transformer-Based AI Model for Predicting Review Helpfulness with Review-Product Relevance

• Best Paper Award, 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, KORMS Fall Conference (2023)
  A Cross-Domain Recommendation Model with Doc2Vec for Solving Data Sparsity Problems

• Excellent Paper Award, KORMS Fall Conference (2023)
  A Personalized Restaurant Recommendation Model Exploiting Granular Customer Preferences

• Best Paper Award, KITSS Spring Conference (2023)
  Development of a Graph Convolutional Network-Based Recommendation System Utilizing Explicit and Implicit Feedback

• Excellent Paper Award, KIISS Spring Conference (2021)
  Enhancing Personalized Recommendation Service Performance through CNN-Based Prediction of Review Helpfulness Scores

Last updated: October 2025