DMCCI 2011: ICDM 2011 Workshop on

Data Mining Technologies for Computational Collective Intelligence

1.  Overview

Computational collective intelligence aims to explore the group intelligence using computational methods. Over the recent years, the ubiquitous use of world wide web and rapid development of internet technology have provided an unprecedented environment of various group activities. Numerous interdisciplinary and interdependent systems are created and used to represent the various biological, social, physical and ecological systems for investigating the interactions between individuals, groups, communities. This requires joint efforts to take advantage of the state-of-the-art research from multiple disciplines develop novel theories, experiments, and methodologies to study these rich interactions as well as make better group decisions.

This workshop will bring together the interdisciplinary researchers from sociology, behavioral science, computer science, psychology, bioinformatics, ecology, cultural study, information systems, operations research to share, exchange, learn, and develop preliminary results, new concepts, ideas, principles, and methodologies on applying data mining technologies for computational collective intelligence, aiming to merge the gap between the two areas, encourage collaborations, advance and deepen our understanding of interactions as well as collective intelligence, and devise more effective and efficient computational algorithms to make wiser decisions.

Final Program

2. Topic of Interests

The topics of this special issue include, but not limit to, the following:

·       Graph and Matrix methods for computational collective science

·       Probabilistic models for collective social science

·       Tensor models for evolving group/community analysis

·       Transfer learning on heterogeneous groups/communities

·       Link analysis and network structure discovery

·       Viral Marketing and influence propagation

·       User behavior modeling

·       Social tagging, blog and forum analysis

·       Security and Privacy issues

·       Query log and click through data analysis

·       Expertise and authority discovery

·       Social navigation and visualization

·       Collaborative filtering and recommendation       

3. Submission Instructions

We invite regular paper submissions, work-in-progress,  and position papers. All papers must follow the IEEE ICDM format and be submitted through

Regular papers can be up to 8 pages in length; short papers, such as position and work-in-progress papers, no more than 6 pages; two additional pages can be purchased for $125 per page. All papers will be reviewed by at least three Program Committee members on the basis of technical quality, relevance to workshop topics, originality, significance, and clarity before the final decision is made.

Key Dates

·        Paper Submission           August 5, 2011

·        Author Notification        September 23, 2011

·        Camera ready                    October 20,2011

·        Workshop                          December 11, 2011


4. Organizers

        General Co-Chairs

·       Charu Aggarwal. IBM T.J. Watson Research Center

·       Tina Eliassi-Rad. Rutgers University.

·       Philip S. Yu. University of Illinois at Chicago


        Program Co-Chairs


·       Hanghang Tong. IBM T.J. Watson Research Center

·       Fei Wang. IBM T.J. Watson Research Center

·       Hong Cheng. The Chinese University of Hong Kong


        Program Committee

·       Leman Akoglu. Carnegie Mellon University.          

·       Yun Chi. NEC Research Lab America at Cupertino.

·       Elizabeth Daly. IBM Research Cambridge.

·       Ian Davidson. University of California, Davis.

·       Brian J. Gallagher. LLNL.

·       Lise Getoor. University of Maryland, College Park.

·       Maxim Gurevich. Yahoo!

·       Jingrui He. IBM T.J. Watson Research Center.

·       Alejandro (Alex) Jaimes. Yahoo! Barcelona.

·       U Kang. Carnegie Mellon University.

·       Kristina Lerman. University of Southern California.

·       Lei Li. Carnegie Mellon University.

·       Haibing Lu. Rutgerts University.

·       Dijun Luo. UT Arlington.

·       Spiros Papadimitriou. Google Research.

·       B. Aditya Prakash. Carnegie Mellon University.

·       Yanghua Shaw. Fudan University.

·       Vikas Sindhwani. IBM T.J. Watson Research Center.

·       Yuan Yao. Nanjing University.

·       Dashun Wang. Northeastern University.

·       Haiyi Zhu. Carnegie Mellon University.