2015年9月19号上午9点，应计算机学院现代数据工程与实时计算（ADE）实验室主任李国徽教授的邀请，新加坡管理大学信息系统学院朱飞达教授在计算机学院南一楼会议室601作了题为“Social media mining and analysis for business, consumer and social insights”的报告。

主讲人简介:Prof. Zhu is an assistant professor in School of Information System, Singapore Management University (SMU). His research interests include large-scale data mining, text mining, graph/network mining and social network analysis. He has published more than 70 quality papers in referred international conferences and journals, including ICDE, VLDB, SIGMOD, WWW, JMLR, TODS, etc. His work on  large-scale frequent pattern mining has won the Best Student Paper Awards at 2007 IEEE International Conference on Data Engineering (ICDE’07) and 2007 Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD’07). Feida is very active in serving the research community. He is a program committee co-chair of SNAKDD (2013/14), Demo Co-Chair of DASFAA'14 and APWeb'14, a tutorial speaker at SIGKDD’14, senior program committee member of CIKM’13, and program committee members of many conferences including WWW’14, ICDM (2012/13/14), ICDE(2012/13), VLDB’12, ACML’12, etc. He has founded the Pinnacle Lab a joint lab with China Ping An Insurance Group to focus on social media mining and analysis for finance industry. He obtained his Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign (UIUC) in 2009, supervised by Prof. Jiawei Han, and his B.Sc. in Computer Science from Fudan University, China, in 2001.

报告的主要内容如下: The recent blossom of social network services has provided every one with an unprecedented level of ease and fun of sharing information of all sorts.  These public social data therefore reveal a surprisingly large amount of information about an individual which is otherwise unavailable. Moreover, the real-time nature of platforms such as Twitter has made them the most important and timely sources to capture viral topics of mass interest, or even the lifeline for millions in midst of natural disasters. The business, consumer and social insights attainable from this big and dynamic social data are critically important and immensely valuable in a wide range of applications for both private and public sectors. Central to this task are two research challenges of equal importance which complement and inform each other: user profiling and event profiling.  In this talk, we will explore a few important topics in this task including network-based user modeling, cross-platform user identity linkage, real-time event detection and profiling.

本次报告吸引了来自学院多个实验室的老师和同学参加，朱飞达教授的报告内容详实、精彩生动，给前来聆听的师生们留下了深刻印象。针对报告的内容，到场的师生也与朱飞达教授进行了进一步地探讨和交流，会场气氛相当热烈。