ICDM 2010 Workshop on Large-scale Analytics for Complex Instrumented Systems (LACIS 2010)

Theme and Topics

Complex instrumented systems are ubiquitous, found in for instance in civil engineering, information systems, health care systems, biological and life sciences, environment monitoring, oil drilling, mobile phones and sensor networks, financial engineering, and social networks. The fundamental notion of complex instrumented systems is about collecting, monitoring and analyzing data in order to generate real-time insight to help people make informed decisions. Learning and data mining has emerged as a key step in the analysis here.  Moreover, it is clear that for systems to have real sustainability, efficiency, and self-awareness for diagnosis and monitoring, learning and data mining are essential.

Large-scale and heterogeneity are key properties of data in complex instrumented systems, whereas real-time response and incremental model update are key requirements. This presents challenges to existing algorithms for machine learning and data mining. In this workshop, we are interested in investigating the scalability and efficiency of machine learning and data mining algorithms with respect to both theoretical and experimental perspectives mining from complex instrumented systems. We are also interested in real world data mining applications and case studies related to complex instrumented systems. The following topics with regards complex instrumented systems are sought:   

• Systems and frameworks for large-scale data mining
• Methodologies for online data mining or stream mining
• Real-time decision support and mining
• Parallel data mining methods and applications
• Scalable data mining algorithms and systems over heterogeneous data sources
• Application areas such as:
  • manufacturing and heavy industry 
  • life science, biology 
  • medical informatics and health care 
  • environmental applications such as climate modeling
  • emerging applications such as web mining, social network analysis
  • other domains such as civil engineering, financial engineering, etc.

Invited Speaker

Important Date

• Submission deadline: August 9th, 2010
• Review period: approximately 3 weeks
• Notification date: September 20th, 2010
• Final version submission date: October 11th, 2010

Submissions

Please prepare your paper not more than 10 pages in PDF file, with IEEE camera‐ready template: http://datamining.it.uts.edu.au/icdm10/index.php/paper-submissions/submission-guidelines.

All papers must be submitted in Adobe Portable Document Format (PDF). Please ensure that any special fonts used are included in the submitted documents. Please use the following link to submit your paper here.

http://wi-lab.com/cyberchair/icdm10/scripts/submitform.php?subarea=SI&undisplay_detail=1&wh=/cyberchair/icdm10/scripts/ws_submit.php

If you cannot submit there, please send to us by email <liuya@us.ibm.com>.

Workshop Co-Chairs

• Chid Apte, IBM TJ Watson 
• Wray Buntine, NICTA Canberra Research Laboratory 
• Yan Liu, IBM TJ Watson 
• Jimeng Sun, IBM TJ Watson
• Jie Tang, Tsinghua University, China 

Program Committee

• Adam Kowalczyk, NICTA
• Rayid Ghani, Accenture
• Charles Elkan, University of California, San Diego
• Jennifer Neville, Purdue University
• Mohammed Zaki, Rensselaer Polytechnic Institute 
• Dong Zhang, Google Inc.
• Lei Zhang, Microsoft Research Asia
• Zhong Su, IBM, CRL
• Xifeng Yan, University of California, San Babara
• Spiros Papadimitriou, IBM
• Tamara Kolda, Sandia National Labs
• Petros Drineas, RPI
• Edwin Pednault, IBM Research
• Elad Yom-Tov, IBM Research
• Philip S. Yu, University of Illinois at Chicago
• Qiang Yang, Hong Kong University of Science and Technology
• Huiming Qu, IBM TJ Watson
• Sanjay Chawla, University of Sydney
• Yu-Ru Lin, ASU

Program 

Contact us

Yan Liu, IBM TJ Watson Research Center, liuya@us.ibm.com, 1-914-945-2128