Research Interests

  • Video and Audio Understanding
  • Recommendation Systems
  • Collaborative Filtering
  • Statistical Machine Learning

Publications

Google Scholar | DBLP | Semantic Scholar
  • Book Chapters
    1. Joonseok Lee. Recommendation Systems: An Industrial Application of Network Big Data for Computational Intelligence, Big Data and Computational Intelligence in Networking, Yulei Wu, Fei Hu, Geyong Min, Albert Y. Zomaya (ed.), CRC Press, ISBN: 9781498784863, Chapter 11, 2017. [link]
  • Referred Journals
    1. Sangho Suh, Sungbok Shin, Joonseok Lee, Chandan K. Reddy, Jaegul Choo. Localized User-Driven Topic Discovery via Boosted Ensemble of Nonnegative Matrix Factorization, Knowledge and Information Systems (KAIS), 2018. [pdf]
    2. Joonseok Lee, Seungyeon Kim, Guy Lebanon, Yoram Singer, Samy Bengio. LLORMA: Local Low-Rank Matrix Approximation, Journal of Machine Learning Research (JMLR) 17(15):1-24, 2016. [pdf]
    3. Joonseok Lee, Hanggjun Cho, Robert Ian (Bob) McKay. A Rapid Screening and Testing Protocol for Keyboard Layout Speed Comparison, IEEE Transactions on Human-Machine Systems, vol.PP, no.99, pp.1-14, 2014. [pdf]
    4. Joonseok Lee, Mingxuan Sun, Guy Lebanon. PREA: Personalized Recommendation Algorithms Toolkit, Journal of Machine Learning Research (JMLR) 13:2699-2703, 2012. [pdf] [code]
  • Referred Conferences
    1. Joonseok Lee, Sami Abu-El-Haija, Balakrishnan Varadarajan, Paul Natsev. Collaborative Deep Metric Learning for Video Understanding, To appear in Proceedings of the 24th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2018. [pdf] [video]
    2. Sangho Suh, Jaegul Choo, Joonseok Lee, Chandan Reddy. Local Topic Discovery via Boosted Ensemble of Nonnegative Matrix Factorization, Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI), Sister Conferences track, 2017. [pdf]
    3. Sangho Suh, Jaegul Choo, Joonseok Lee, Chandan Reddy. Boosted L-EnsNMF: Local Topic Discovery via Ensemble of Nonnegative Matrix Factorization, Proceedings of the IEEE International Conference on Data Mining (ICDM), 2016. Best Student Paper Award [pdf]
    4. Joonseok Lee, Ariel Fuxman, Bo Zhao, Yuanhua Lv. Leveraging Knowledge Bases for Contextual Entity Exploration, Proceedings of the 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2015. [pdf]
    5. Seungyeon Kim, Joonseok Lee, Guy Lebanon, Haesun Park. Local Context Sparse Coding, Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI), 2015. [pdf]
    6. Seungyeon Kim, Joonseok Lee, Guy Lebanon, Haesun Park. Estimating Temporal Dynamics of Human Emotions, Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI), 2015. [pdf]
    7. Joonseok Lee, Samy Bengio, Seungyeon Kim, Guy Lebanon, Yoram Singer. Local Collaborative Ranking, Proceedings of the 23rd International World Wide Web Conference (WWW), 2014. Best Student Paper Award [pdf]
    8. Joonseok Lee, Seungyeon Kim, Guy Lebanon, Yoram Singer. Local Low-Rank Matrix Approximation, Proceedings of the 30th International Conference on Machine Learning (ICML), 2013. [pdf]
    9. Joonseok Lee, Seungyeon Kim, Guy Lebanon, Yoram Singer. Matrix Approximation under Local Low-Rank Assumption, The Learning Workshop in International Conference on Learning Representations (ICLR), 2013. [pdf]
    10. Mingxuan Sun, Fuxin Li, Joonseok Lee, Ke Zhou, Guy Lebanon, Hongyuan Zha. Learning Multiple-Question Decision Trees for Cold-Start Recommendation, Proceedings of the 6th ACM International Conference on Web Search and Data Mining (WSDM), 2013. [pdf]
    11. Joonseok Lee, Mingxuan Sun, Seungyeon Kim, Guy Lebanon. Automatic Feature Induction for Stagewise Collaborative Filtering, Advances in Neural Information Processing Systems (NIPS) 25, 2012. [pdf]
    12. Joonseok Lee, Hanggjun Cho, Robert Ian (Bob) McKay. Rapid Screening of Keyboard Layouts, Proceedings of IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2012. [pdf]
    13. Joonseok Lee, Robert Ian (Bob) McKay. Optimizing a Personalized Cellphone Keypad, Proceedings of the 5th International Conference on Convergence and Hybrid Information Technology (ICHIT), 2011. [pdf]
  • Workshops, Demos, and ArXiv Preprints
    1. Sami Abu-El-Haija, Amol Kapoor, Bryan Perozzi, Joonseok Lee. N-GCN: Multi-scale Graph Convolution for Semi-supervised Node Classification, ArXiv Report arXiv:1802.08888, 2018. [pdf]
    2. Joonseok Lee, Sami Abu-El-Haija. Large-Scale Content-Only Video Recommendation, CEFRL Workshop at the International Conference on Computer Vision (ICCV), 2017. [pdf]
    3. Joonseok Lee, Nisarg Kothari, Paul Natsev. Content-based Related Video Recommendations, Advances in Neural Information Processing Systems (NIPS) Demonstration Track, 2016. [pdf]
    4. Sami Abu-El-Haija, Nisarg Kothari, Joonseok Lee, Paul Natsev, George Toderici, Balakrishnan Varadarajan, Sudheendra Vijayanarasimhan. YouTube-8M: A Large-Scale Video Classification Benchmark, ArXiv Report arXiv:1609.08675, 2016. [pdf] [blog post]
    5. Joonseok Lee, Kisung Lee, Jennifer G. Kim, Sookyung Kim. Personalized Academic Research Paper Recommendation System, Proceedings of the 6th International Workshop on Social Recommender Systems (SRS), 2015. [pdf]
    6. Joonseok Lee, Mingxuan Sun, Guy Lebanon. A Comparative Study of Collaborative Filtering Algorithms, ArXiv Report arXiv:1205.3193, 2012. [pdf]
    7. Kiyeon Lee, Joonseok Lee, Hyunwoong Shin, Sunghwan Kim, Jungwoo Choi. Real-Time Motion Tracking System using Omni-Directional PTZ Camera, Small and Medium Business Administration of South Korea, 2006. [pdf]
  • Theses
    1. Joonseok Lee. Local Approaches for Collaborative Filtering, Georgia Institute of Technology (Ph.D. Dissertation), 2015. [pdf]
    2. Joonseok Lee. Merging Algorithm for Unified Communicator, Seoul National University (Bachelor's Thesis), 2009. [pdf]

Talks and Presentations


Academic Activities


Ongoing Projects

  • Video contents analysis and recommendation

Past Projects

  • Local Collaborative Ranking
  • Local Low-Rank Matrix Approximation
  • Local Context Sparse Coding
  • Graph-based Context-aware Entity Recommendation
  • Ensembles of collaborative filtering algorithms
  • Comparative study of collaborative filtering algorithms
    • Full experimental results (to be added soon)
  • PREA (Personalized Recommendation Algorithms) Toolkit
  • Mood analysis for blog texts

Frequent Collaborators