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Broad Learning on Big Data via Fusion of Heterogeneous Information

主讲人 :Philip S. Yu教授 地点 :科研楼610 开始时间 : 2018-12-20 14:00 结束时间 : 2018-12-20 15:00

Abstract

Looking from a global perspective, the landscape of online social networks is highly fragmented. A large number of online social networks have appeared, which can provide users with various types of services. Generally, information available in these online social networks is of diverse categories, which can be represented as heterogeneous social networks (HSNs) formally. Meanwhile, in such an age of online social media, users usually participate in multiple online social networks simultaneously, who can act as the anchors aligning different social networks together. So multiple HSNs not only represent information in each social network, but also fuse information from multiple networks. 

Formally, the online social networks sharing common users are named as the aligned social networks, and these shared users are called the anchor users. The heterogeneous information generated by users’ social activities in the multiple aligned social networks provides social network practitioners and researchers with the opportunities to study individual user’s social behaviors across multiple social platforms simultaneously.

 

Bio

Philip S. Yu is a pioneer and leading research in big data, data mining (especially on graph/network mining), social network, privacy preserving data publishing, data stream, database systems, and Internet applications and technologies. He is a Distinguished Professor in the Department of Computer Science at UIC and also holds the Wexler Chair in Information and Technology. Before joining UIC, he was with IBM Thomas J. Watson Research Center, where he was manager of the Software Tools and Techniques department. Dr. Yu has published more than 970 papers in refereed journals and conferences with more than 74,500 citations and an H-index of 127. He holds or has applied for more than 300 US patents.

Dr. Yu is a Fellow of the ACM and the IEEE. He is the recipient of ACM SIGKDD 2016 Innovation Award, IEEE Computer Society's 2013 Technical Achievement Award, Research Contributions Award from IEEE International Conference on Data Mining (ICDM) in 2003 for his pioneering contributions to the field of data mining. He also received an IEEE Region 1 Award for "promoting and perpetuating numerous new electrical engineering concepts" in 1999. 

Dr. Yu was the Editor-in-Chief of ACM Transactions on Knowledge Discovery from Data and was the Editor-in-Chief of IEEE Transactions on Knowledge and Data Engineering (2001-2004). He is on the steering committee of ACM Conference on Information and Knowledge Management and was a steering committee member of the IEEE Conference on Data Mining and the IEEE Conference on Data Engineering. He also served as the associate editor, general chair or co-chairs and steering committee for a series of top journals and top conferences.

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