Mining Geo-Social Networks - Mining 4W (What, Who, When, Where)
报告题目:Mining Geo-Social Networks - Mining 4W
(What, Who, When, Where)
报告人: 阴红志博士 澳洲优秀青年基金获得者（ARC DECRA Fellow）
时间: 2016年1月21日上午 10:00
The rapid development of Web 2.0, location acquisition and wireless communication technologies has fostered a profusion of geo-social networks, such as location-based social networks (LBSNs) and event-based social networks (EBSNs). Typical geo - social networking sites allow users to “check in” at a physical place and share their locations and specific activities with their online friends, and therefore bridge the gap between the real world and online social networks. The availability of large amounts of geographical and social data on geo-social networks provides an unprecedented opportunity to study human mobility and interests in a spatial-temporal-social context, enabling a variety of geo-social mining tasks, such as mobile recommendation, information diffusion on geo-social network, location inference, community discovery and link prediction. In this report, I first introduce the background and framework of geo-social networking. I next discuss the distinct properties, data analysis and research issues of geo-social networks, and present two illustrative examples to show the application of data mining to real-world geo-social networks: Spatial Item Recommendation and Community Discovery.
Dr. Hongzhi Yin works as an ARC DECRA Fellow with The University of Queensland, Australia. From Sept 2014 to December 2015, he has been working as post-doc research fellow at School of Information Technology and Electrical Engineering, the University of Queensland, Australia, Supervised byProf. Xiaofang Zhou. He received his doctoral degree from Peking University in July 2014. During his graduate program, he worked at Institute of Network Computer and Information System, EECS, Peking University, under the supervision of Prof. Bin Cui. From March 2013 to December 2014, he worked as a visiting researcher at QCIS:UTS, under the supervision of Prof. Chengqi Zhang and Dr. Ling Chen. From June 2012 to December 2012, he worked as a research intern in Microsoft Research Asia (MSRA) and his mentor was Prof. Jirong Wen. His current main research interests include user behavior modeling, user profiling, recommender system, especially spatial-temporal recommendation, topic discovery and event detection, deep learning. He has published over 30 papers as the main author, and most of them has been published in reputed journals and top international conferences including ACM TOIS, ACM TKDD, ACM SIGMOD, ACM SIGKDD, VLDB, IEEE ICDE, ACM SIGMM and CIKM.
活动宣传：阴红志博士作《Mining Geo-Social Networks-Mining 4W(What, Who, When, Where)》报告