Hoon Park

Recommendation System, Data Mining, Transfer Learning, Heterogeneous Domain, Generative Adversarial Network

Education

M.S., Chung-Ang University, Major in Big Data, Department of Computer Science and Engineering, (Feb 2022 - Feb 2024)
Thesis: Generative Latent Feature Extraction for Cross-Domain Mediation in Recommendation Systems
B.S., Soonchunhyang University, Department of Computer Software Engineering, (Feb 2016 - Feb 2022)

Smart Tourism Platform Development with Meta-Path Embedding Recommendation System
Ministry of SMEs and Startups (MSS, Korea), (May 2022 - May 2023)
AI-based Cloud Service (AlaaS) Technology for Anomaly Pattern Detection in Multi-data Streams
Ministry of Education, (Oct 2022 - Jan 2023)
Survey Recommender
Knowledge Engineering Lab, (June 2022 - July 2022)
Two-State Based Collaborative Filtering for Perfume Recommendation (MYFUME)
Soonchunhyang university, (May 2020 - May 2021)
Health checkup guide
Industry-university cooperation foundation, Soonchunhyang university, (Aug 2017 - Dec 2017)
Pictogram
GameMakers [Unity Certified Club], (Aug 2017 - Dec 2017)

Yu Seung Kang, Hoon Park, “LVGAN: Latent Vector Embedding for Generative Adversarial Network of Recommender Systems”, European Conference on Artificial Intelligence (ECAI), Submit
Hoon Park, Jason J. Jung, "HeteLFX: Heterogeneous Recommendation with Latent Feature Extraction", Electronic Commerce Research and Applications (ECRA),
DOI: 10.1016/j.elerap.2024.101419 [Link]
Hoon Park, Jason J. Jung, "Latent Mutual Feature Extraction for Cross-domain Recommendation", Knowledge and Information Systems (KAIS),
DOI: 10.1007/s10115-024-02065-y [Link]

Hoon Park, Jason J. Jung, “Methods and devices for item recommendation using cross-domain information extraction”, 12/2023, Submit
Young Hyun Kim, Hyeon Seok Lee, Yu Seung Kang, Hoon Park, Jason J. Jung, "APPARATUS, METHOD AND SYSTEM FOR CUSTOMIZED TRACK RECOMMENDATION", 04/2023, Submit
Hoon Park, Ji Hoon Park, "Smart cradle". Ref. No: KR 1025189290000, 04/2023 [Link]
Hoon Park, Ji Hoon Park, "Lost and found system". Ref. No: KR 1020587950000, 12/2019 [Link]