An invited talk by Prof. Zhipeng Zhang, Associate Professor, Liaoning Normal University, China, will be held on October 19, 2022, at Zoom (online). Prof. Zhipeng Zhang will share some interesting ideas about Recommender systems and their applications and challenges.

Date: 19 Oct 2022
Time: 08:45 AM to 10:15 AM (JST)

Location:

https://zoom.us/j/7701243471?pwd=ZFcrcmNPbmxtRC9qbTlackc3bWdtZz09

CO-ORGANIZED BY:

IEEE Muroran Institute of Technology Student Branch

IEEE Sapporo Section Young Professionals (YP)

Emerging Networks and Systems Laboratory (ENeS), Muroran Institute of Technology

Topic: Recommender systems and their applications and challenges

Abstract:

Recommender system (RS) can help users optimize the search results and generate personalized recommendations from mass data, so as to further alleviate the problem of information overload. Currently, RS gradually becomes a core application around our daily life, such as news feed, online shopping, and urban point-of interest. However, existing RSs face many challenges, such as cold-start and over-fitting. This report gradually introduces three solutions for RSs. First, how to alleviate new user cold-start in user-based collaborative filtering via bipartite network. Second, how to solve over-fitting problem in RSs via link-based collaborative filtering. Finally, how to enhance the accuracy for urban point-of-interest recommendations via context-enhanced probabilistic diffusion.