2023年11月15日（星期三）13:30演講訊息如下，歡迎踴躍參加!!

演講題目：Novel Personalized Multimedia Recommendation Systems Using Tensor Singular-Value-Decomposition

演  講  者：Prof. Shih Yu Chang, San Jose State University, San Jose, CA, USA

時　　間：13:30~15:30, 2023/11/15 (Wednesday)

地　　點：清華大學台達館304室 (Delta Building R304, NTHU)

ABSTRACT

Because of rapid growth of multimedia data over the Internet, the infobesity has been emerging in recent years. Many recommender systems (RSs) have been proposed using a variety of techniques, including artificial intelligence, machine learning, statistical analysis, and data mining. Nowadays, E-commerce companies such as Amazon, eBay, Netflix, etc. have applied RSs conveniently to provide better customer services than before by enabling customized multimedia-content recommendations. It is well known that classical RSs are almost all based on the user-item attribute matrices. However, this two-fold user-item relationship should be extended to the emerging many-fold relationship among an arbitrary number of attribute groups so that the corresponding new RSs may lead to better performances. Therefore, in this paper, we introduce a novel personalized multimedia recommender system (PMRS) according to our proposed new parallel higher-order tensor singular-value-decomposition (PHOTSVD) algorithm. This PHOTSVD algorithm is capable of accommodating an arbitrary number of entities such as social-media channels, users, queries, webpages, etc. in a robust RS. Furthermore, we also investigate the cold start and data bias problems critical to RSs. Finally, we compare the performances of our proposed new PMRS and three other existing tensor-based RSs over real world data with respect to the well-adopted metric, namely normalized root-mean-square error (NRMSE). Our proposed new PMRS greatly outperforms the other three existing tensor-based RSs in terms of NRMSE.

BIOGRAPHY

Shih Yu Chang received a B. S. E. E. degree from National Taiwan University, Taiwan, in 1998, and Ph. D. degrees in electrical engineering and computer engineering from University of Michigan, Ann Arbor, in 2006. From August 2006 to February 2016, he was the faculty in the Department of Computer Engineering, National Tsing Hua University, Hsinchu, Taiwan. From July to August 2007, Dr. Chang had been a visiting assistant professor at Television and Networks Transmission Group, Communications Research Centre, Ottawa, Canada. From June 2018, he began to provide lectures about machine learning, data science, and AI in San Jose State University, San Jose, CA, USA. Besides academic positions, Dr. Chang also provides consulting work as an AI technical lead focusing on applying machine learning techniques to automate office work.

Dr. Chang has published more than 100 peer-refereed technical journals and conference articles in electrical and computer engineering. His research interests include the areas of wireless networks, wireless communications and signal processing. He currently serves as the technical committee, symposium chair, track chair, or the reviewer in networking, signal processing, communications, and computers.