BigMine-13: Call for Participation

[Erheng Zhong]

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                   CALL FOR PARTICIPATION

                  In conjunction with KDD 2013

                   2nd International Workshop on 

Big Data, Streams and Heterogeneous Source Mining: 

                        Algorithms, Systems, 

              Programming Models and Applications

                          --- BigMine 2013 ---

                     Chicago - August 11, 2013

                       http://bigdata-mining.org/

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AIM and SCOPE

=============

Our ability to collect data in various sensors, devices, formats, either from independent or connected applications, has significantly outpaced our capability to process, analyze, store and understand these datasets. Considering Internet data, the web pages indexed by Google were 1 million in 1998, but quickly reached 1 billion in 2000 and have exceeded 1 trillion in 2008. Recently, the flourish of social networking applications, like Facebook, Twitter, that allow users to create contents freely, further amplifies the already huge web volume. Furthermore, with mobile phones becoming the sensory gateway to get real-time data on people from different aspects, the vast amount of data that mobile carrier can potentially process to improve our daily life has significantly outpaced our past CDR (call data record)-based processing for billing purposes only. It can be foreseen that Internet of things (IoT) applications will raise the scale of data to an unprecedented level. People and devices (from home coffee machines to cars, to buses, railway stations and airports) are all loosely connected. Trillions of such connected components will generate a huge data ocean, and valuable information must be discovered from the data to help improve quality of life and make our world a better place. For example, after we get up every morning, in order to optimize our commute time to work and complete the optimization before we arrive at office, the system needs to process information from traffic, weather, construction, police activities to our calendar schedules, and perform deep optimization under the tight time constraints. In all these applications, we are facing significant challenges in leveraging the vast amount of data, including challenges in (1) system (2) algorithm (3) business model – application. This workshop aims to bring together people from both academia and industry to present their most recent work related to these issues, and exchange ideas and thoughts in order to advance this big challenge that has been considered as one of the most exciting opportunities in the past 10 years.

PROGRAM

=======

The Workshop program is accessible at: http://bigdata-mining.org/schedule/

WORKSHOP VENUE

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The workshop will take please at Room Chicago 9, Chicago Sheraton Hotel

PROGRAM CHAIRS

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Wei Fan -- Huawei Noah’s Ark Lab

Albert Bifet -- Yahoo! Research Barcelona

Qiang Yang -- Huawei Noah’s Ark Lab

Philip Yu -- University of Illinois at Chicago

ORGANIZERS

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Albert Bifet, Yahoo! Research Barcelona

Wei Fan, Huawei Noah’s Ark Lab

Jing Gao, University at Buffalo

Le Gruenwald, National Science Foundation, University of Oklahoma

Dimitrios Gunopulos, University of Athens

Geoff Holmes, University of Waikato

Latifur Khan, University of Texas at Dallas

Dekang Lin, Google

Deepak Turaga, IBM T.J. Watson Research

Qiang Yang, Huawei Noah’s Ark Lab

Philip Yu, University of Illinois at Chicago

Kun Zhang, Xavier University of Louisiana

Xiatian Zhang, Tencent

Yuanchun Zhou, Chinese Academy of Sciences

PROGRAM COMMITTEE

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Vassilis Athitsos, University of Texas at Arlington

Roberto Bayardo, Google

Francesco Bonchi, Yahoo! Research Barcelona

Liangliang Cao, IBM

Hong Cheng, The Chinese University of Hong Kong

Alfredo Cuzzocrea, ICAR-CNR & University of Calabria

Ian Davidson, SUNY

Nan Du, Georgia Institute of Technology

Joao Gama, University Porto

Fosca Giannotti, ISTI-CNR

Aristides Gionis, Yahoo! Research Barcelona

Bart Goethals, University of Antwerp

Jiawei Han, University of Illinois at Urbana-Champaign

Marwan Hassani, Aachen University

Steven C.H. Hoi, Nanyang Technological University

Siddhartha Jonnalagadda, Mayo Clinic

Murat Kantarcioglu, University of Texas at Dallas

George Karypis, University of Minnesota

Steve Ko, SUNY at Buffalo

Vipin Kumar, University of Minnesota, Twin Cities

Jianhui Li, Computer Network Information Center,Chinese Academy of Sciences

Cindy Xide Lin, University of Illinois at Urbana-Champaign

Shou-De Lin, National Taiwan University

Michael May, Fraunhofer IAIS

Themis Palpanas, University of Trento

Bernhard Pfahringer, University of Waikato

Jesse Read, Universidad Carlos III

Chandan K. Reddy, Wayne State University

Cyrus Shahabi, USC

Ashok Srivastava, NASA

Jian-Tao Sun, Microsoft Research Asia

Jie Tang, Tsinghua University

Hanghang Tong, Carnegie Mellon University

Haifeng Wang, Baidu

Bo Wang, Nanjing University of Aeronautics & Astronautics

Yi Wang, Tencent

Xian Wu, Microsoft

Tian Wu, Baidu

Zhenghua Xue, Chinese Academy of Sciences

Gui-Rong Xue, Shanghai Jiao Tong University

Xifeng Yan, University of California at Santa Barbara

Rong Yan, Facebook

Aden Yuen, Tencent

Demetris Zeinalipour, University of Cyprus

Xingquan Zhu, University of Technology, Sydney

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Thanks and best regards,
Erheng Zhong (钟迩桁),

Department of Computer Science and Engineering, HKUST

[Erheng Zhong]

Sorry for cross-posting. 

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                   CALL FOR PARTICIPATION

                  In conjunction with KDD 2013

                   2nd International Workshop on 

Big Data, Streams and Heterogeneous Source Mining: 

                        Algorithms, Systems, 

              Programming Models and Applications

                          --- BigMine 2013 ---

                     Chicago - August 11, 2013

                       http://bigdata-mining.org/

-------------------------------------------------------------------------

PROGRAM

=======

The Workshop program is accessible at: http://bigdata-mining.org/schedule/

9:00 to 9:15 Opening Remarks

9:15 to 10:00 Keynote: Hong Cheng, Processing Reachability Queries with Realistic Constraints on Massive Networks

10:00 to 10:30 Coffee Break

10:30 to 11:15 Invited Talk: Xavier Amatriain, Netflix Big & Personal: the data and the models behind Netflix recommendations

11:15 to 12:00 Keynote: Christos Faloutsos, Large Graph Mining – Patterns, tools and cascade analysis

12:00 to 12:10 PM Best Paper Award.

12:10 to 2:00 PM Lunch

2:00 to 2:45 PM Keynote: Jiawei Han, Challenging Problems for Scalable Mining of Heterogeneous Social and Information Networks

2:45 to 3:15 PM Paper Highlight

3:15 to 3:30 PM Concluding Remarks

3:30 to 4:00 PM Coffee Break and Poster Set up

4:00 to 5:00 PM Poster Session

AIM and SCOPE

=============

Our ability to collect data in various sensors, devices, formats, either from independent or connected applications, has significantly outpaced our capability to process, analyze, store and understand these datasets. Considering Internet data, the web pages indexed by Google were 1 million in 1998, but quickly reached 1 billion in 2000 and have exceeded 1 trillion in 2008. Recently, the flourish of social networking applications, like Facebook, Twitter, that allow users to create contents freely, further amplifies the already huge web volume. Furthermore, with mobile phones becoming the sensory gateway to get real-time data on people from different aspects, the vast amount of data that mobile carrier can potentially process to improve our daily life has significantly outpaced our past CDR (call data record)-based processing for billing purposes only. It can be foreseen that Internet of things (IoT) applications will raise the scale of data to an unprecedented level. People and devices (from home coffee machines to cars, to buses, railway stations and airports) are all loosely connected. Trillions of such connected components will generate a huge data ocean, and valuable information must be discovered from the data to help improve quality of life and make our world a better place. For example, after we get up every morning, in order to optimize our commute time to work and complete the optimization before we arrive at office, the system needs to process information from traffic, weather, construction, police activities to our calendar schedules, and perform deep optimization under the tight time constraints. In all these applications, we are facing significant challenges in leveraging the vast amount of data, including challenges in (1) system (2) algorithm (3) business model – application. This workshop aims to bring together people from both academia and industry to present their most recent work related to these issues, and exchange ideas and thoughts in order to advance this big challenge that has been considered as one of the most exciting opportunities in the past 10 years.