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新加坡管理大学Jialie Shen副教授学术讲座

报告时间

 

Speaker: Jialie Shen, Assistant Professor, Singapore Management University

Time:  9:00-10:30 am, June 23

Venue: Room 202, Second Floor, Office Building, Software Campus

Host: Jun Ma

 

Title: Just-for-Me: Towards Intelligent Location-Aware Social Music Recommendation

 

Abstract:  As the building block of any living organisms, the cells enjoy an amazing capability to adapt themselves to the environment changes. However, this is very challenging for the existing music recommender systems, especially those under mobile environment. While a large amount of research efforts have been invested in the promising field, the technology is still in its infancy. One of key reasons is that current solutions suffer from the inability to effectively take multiple kinds of contextual information into account. In this talk, I shall introduce Just-for-Me recommender system with a layered structure based on advanced audio analytics scheme and topic model. This architecture enables 1) straightforward and effective incorporation of multiple contextual information about location and global popularity trend and 2) systematically overcome cold-start and sparsity problems. An extensive experimental study demonstrates that Just-for-Me system can significantly improve the recommendation quality from different aspects (e.g., accuracy and robustness) over various geo-locations.

 

Bio:  Dr. Jialie Shen is an Assistant Professor in Information Systems and Lee Foundation Fellow, School of Information Systems, Singapore Management University, Singapore. He received his PhD in Computer Science from the University of New South Wales (UNSW), Australia in the area of large-scale media retrieval and database access methods. He worked as a faculty member at UNSW, Sydney and researcher at information retrieval research group, the University of Glasgow for a few years, before moving to the SMU, Singapore. Dr. Shen’s main research interests include information retrieval, economic-aware media analysis, and statistical machine learning. His recent work has been published or is forthcoming in leading journals and international conferences including ACM SIGIR, ACM Multimedia, ACM SIGMOD, CVPR, ICDE, WWW, IEEE Transactions on Circuits and Systems for Video Technology (IEEE TCSVT), IEEE Transactions on Multimedia (IEEE TMM), IEEE Transactions on Cybernetics (Previously IEEE TMC-B), ACM Transactions on Internet Technology (ACM TOIT) and ACM Transactions on Information Systems (ACM TOIS).

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