About My Research

To provide users a better way of obtaining the contents stored in digital libraries or digital archives, it is important to optimize the information filtering method in those applications. Until now, my research mainly focuses on providing personalized information of Ukiyo-e database of Art Research Center (ARC). Recently I'm working on building knowledge graph that include both ARC dataset and other open source datasets, to recommend contents that are interesting and are with precision.

Biography

2018.4 - now
Graduate School of Information Science and Engineering, Ph.D., Ritsumeikan University, Japan
2016.4 - 2018.3
Graduate School of Information Science and Engineering, M.Eng., Ritsumeikan University, Japan

Research Interests

  • Digital Library
  • Recommender Systems
  • Machine Learning
  • Digital Humanities
  • Information Retrieval
  • Neural Networks

Publications

Jiayun Wang, Biligsaikhan Batjargal, Akira Maeda and Kyoji Kawagoe

2018

"A Recommender System in Ukiyo-e Digital Archives for Japanese Art Novices."  
In Proceedings of the ICADL 2018 (pp.205-209). Springer.

Jiayun Wang, Kyoji Kawagoe

2018

"A Recommender System for Ancient Books, Pamphlets and Paintings in Ritsumeikan Art Research Center Database."  
In Proceedings of the ICCAE 2018 (pp.53-57). ACM.

Jiayun Wang, Kyoji Kawagoe

2017

"Ukiyo-e Recommendation based on Deep Learning for Learning Japanese Art and Culture."  
In Proceedings of the ICISDM'17 (pp.119-123). ACM.

Jiayun Wang, Kyoji Kawagoe

2017

"Ukiyo-e recommender system using restricted Boltzmann machine."  
In Proceedings of the iiWAS 2017 (pp.171-175). ACM.

Pritish Patil, Jiayun Wang, Yuya Aratani, Kyoji Kawagoe

2017

"Prototyping a Recommendation System for Ukiyo-e using Hybrid Recommendation Algorithm."  
In Proceedings of the ICDIM 2017 (pp.298-303). IEEE.

Research Project

2017~

Global Actions for Japanese Cultural Resources

Jiayun Wang — gr0278vx@ed.ritsumei.ac.jp