Social Networks Mining and Search

Time: 13:30 - 15:00 (90 mins)
Date: Monday, March 30, 2009
Venue: Room 5

• ICDE2009 Program Overview

Social networking services and sites are florishing around the world, and they are changing the landscape of how we communicate and interact with each other. Sites such as MySpace, Facebook, and Orkut attract more than ten-billion visits per day. According to the statistics of Google OpenSocial, about one billion users have registered on social networking sites. With the enormous amount of social interaction data, social network analysis has emerged as an important technique to mine relationships among users, and the mined information can be used on a range of applications from improving information retrieval quality, conducting viral marketing, to finding domain-specific experts.

This panel will discuss two data engineering research issues: social-network data mining and social signals for personalizing search. A social network can be formulated into a large graph of nodes, where each node represent a user and a link represents relationship between users. Though some traditional graph mining techniques can be employed to mine user relationship, they are not scalable to deal with millions and billions of nodes. Besides, a relationship can be beyond the traditional “relevance” model. For instance, a relationship can reflect influence and degree of influence; and relationship can change according to the “state” of nodes. This panel will discuss what social signals are potentially useful and how the signals can be mined in a scalable fashion. In particular, the panel will discuss how social signals can help improve Web search.

• Irwin King, The Chinese University of Hong Kong, Hong Kong [ pdf ]

• Christos Faloutsos
  Professor
  Electrical and Computer Engineering
  Carnegie Mellon University
  USA
  [ Audio Introduction | ]
  Christos Faloutsos is a Professor at Carnegie Mellon University. He has received the Presidential Young Investigator Award by the National Science Foundation (1989), the Research Contributions Award in ICDM 2006, nine ``best paper'' awards, and several teaching awards. He has served as a member of the executive committee of SIGKDD; he has published over 160 refereed articles, 11 book chapters and one monograph. He holds five patents and he has given over 20 tutorials and over 10 invited distinguished lectures.
  
  His research interests include data mining for streams and networks, fractals, indexing for multimedia and bio-informatics data, and database performance.
  

• Chin-Yew Lin
  Lead Researcher/Research MGR.
  Microsoft Research Asia
  China
  [ Audio Introduction | pdf | Audio Presentation ]
  Dr. Chin-Yew Lin is a lead researcher and research manager at Microsoft Research Asia (MSRA). He is also the co-director of the MOE/MSRA Information Technology Key Lab at Hong Kong University of Science and Technology (HKUST). Before joining Microsoft in 2006, he was a research scientist at the Information Sciences Institute at the University of Southern California (USC/ISI) where he worked in the Natural Language Processing and Machine Translation (MT) group since 1997. His research interests are automated summarization, question answering, community intelligence, and computational advertising. He also developed automatic evaluation technologies for summarization, QA, and MT. In particular, he created the ROUGE automatic summarization evaluation package. It has become the de facto standard in summarization evaluations. More than 200 research sites worldwide have downloaded this package.

• Cong Yu
  Research Scientist
  Yahoo! Research
  USA
  [ Audio Introduction | pdf | Audio Presentation ]
  Cong Yu is a Research Scientist at Yahoo! Research in New York City. His current research interests are information discovery and exploration on social content sites, and web-scale information extraction. He co-leads the Royal Jelly project at Yahoo! on social content exploration and recommendation, and is a core member of the Purple SOX project on information extraction. He graduated from the Department of EECS at University of Michigan in 2007, with a Ph.D. Degree in Computer Science and Engineering. His doctoral dissertation, Managing Complex Databases in a Schema Management Framework, received ACM SIGMOD Distinguished Dissertation Award Honorable Mention in 2008. He has served on various conference Program Committees since graduation, and is currently co-chairing the Developers Track of the 2009 International World Wide Web Conference. He is an avid fan of Michigan football.
  

• Philip Yu
  Professor and Wexler Chair in Information Technology
  Department of Computer Science
  University of Illinois at Chicago
  USA
  [ Audio Introduction | | Audio Presentation ]
  Philip S. Yu received the M.S. and Ph.D. degrees in E.E. from Stanford University, and the M.B.A. degree from New York University. He is a Professor in the Department of Computer Science at the University of Illinois at Chicago and also holds the Wexler Chair in Information Technology. Dr. Yu spent most of his career at IBM, where he was manager of the Software Tools and Techniques group at the Thomas J. Watson Research Center. His research interests include data mining, Internet applications and technologies, database systems, parallel and distributed processing, and performance modeling. Dr. Yu has published more than 530 papers in refereed journals and conferences. He holds or has applied for more than 350 US patents.
  
  Dr. Yu is a Fellow of the ACM and the IEEE. He is associate editors of ACM Transactions on the Internet Technology and ACM Transactions on Knowledge Discovery from Data. He is on the steering committee of IEEE Conference on Data Mining and was a member of the IEEE Data Engineering steering committee. He was the Editor-in-Chief of IEEE Transactions on Knowledge and Data Engineering (2001-2004). He has received several IBM honors including 2 IBM Outstanding Innovation Awards, an Outstanding Technical Achievement Award, 2 Research Division Awards and the 94th plateau of Invention Achievement Awards. He was an IBM Master Inventor. Dr. Yu received a Research Contributions Award from IEEE Intl. Conference on Data Mining in 2003 and also an IEEE Region 1 Award for “promoting and perpetuating numerous new electrical engineering concepts” in 1999.
  

• The panel is 90 minutes in length
• The panel moderator will have 15 minutes to introduce the panel topic
• Each panelist will be given up to 15 minutes to present their views/opinion/work on the panel topic
• The remaining time will be open mic for the audience