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Information Network Embedding for a New Generation of Geosocial Recommendations

2019-11-26edit:rjyw


Time:15:30-17:00 Tuesday, 26 November 2019

Venue:Lecture Hall (二楼圆形报告厅),Level 2, Admin Building, Software Campus, Shandong University

Speaker:Dr.Hongzhi Yin,the University of Queensland

Title:Information NetworkEmbedding for a New Generation of Geosocial Recommendations

Abstract:The rapid development of mobile Internet, location acquisition and 5G communication technologies has fostered a profusion of geo-social networks (e.g., Foursquare, Yelp and Google Place). They provide users an online platform to check-in at points of interests (e.g., cinemas, galleries and hotels) and share their life experiences in the physical world via mobile devices. The new dimension of location implies extensive knowledge about user behaviors and interests by bridging the gap between online social networks and the physical world. It is crucial to develop new geo-social recommendation services for both individual users and groups to explore the new places, attend new events and find their potential partners to attend these events together. This keynote will introduce three emerging geo-social recommendation paradigms and their new challenges: spatial item recommendation for mobile users, spatial item recommendation for dynamic groups, and joint spatial item and partner recommendation. This keynote will also explore how to adopt and advance the network embedding techniques to address the new challenges in the three geo-social recommendation services.

Short bio: Dr Hongzhi Yin is a senior lecturer (equivalent to Associate Professor in North America) and deputy director of Master program of computer Science with the University of Queensland and the winner of Australian Discovery Early Career Researcher Award (equivalent to NSF CAREER award in North America). He has been focusing on creating big commercial and social values from big user data and sensor data by developing innovative machine learning, data mining and database techniques, including deep learning, spatial-temporal data mining, probabilistic graphical model, recommender systems, social media analytics and mining, time series data mining and prediction, network embedding and mining, and smart sales and smart transportation. He has published 110+ papers and won 5 Best Paper Awards such as ICDE'19 Best Paper Award and ACM Annual Best Computing Award as the main author, and most of his research works have been published in reputed journals and top international conferences including VLDB Journal, ACM TOIS, IEEE TKDE, ACM TKDD, ACM TIST, SIGMOD, SIGKDD, PVLDB, ICDE, AAAI, IJCAI, SIGIR, WWW, ICDM, ACM Multimedia and CIKM. For more details about Dr. Hongzhi Yin, please refer to his homepagehttps://sites.google.com/site/dbhongzhi/.