LACIS 2010 - Workshop on Large-scale Analytics for Complex Instrumented Systems (LACIS 2010)
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Website datamining.it.uts.edu.au/icdm10/index.php/workshops |
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Category LACIS 2010
Deadline: July 23, 2010 | Date: December 13, 2010
Venue/Country: Sydney, Australia
Updated: 2010-06-04 19:32:22 (GMT+9)
Call For Papers - CFP
Complex instrumented systems are ubiquitous around the world, such as civil engineering, information systems, health care systems, biological and life science, financial engineering and social networks. The fundamental notion of complex instrumented systems is about collecting, monitoring, analyzing data from everywhere and generating real-time insight to help people to make the informed decisions. Learning and mining from complex instrumented systems, such as environment monitoring, oil drilling, health care, sensor network, has emerged as one of the most important and challenging areas for sustainable development. Large-scale and heterogeneity are the key properties of data in complex instrumented systems. Real-time response and incremental model update are the key requirements for the analysis in complex instrumented systems. This raises great challenges to the existing algorithms on 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. We seek papers in the following topics: Systems and frameworks for large-scale data miningMethodologies for online data mining or stream miningReal-time decision support and miningParallel data mining methods and applicationsScalable data mining algorithms and systems over heterogeneous data sourcesData Mining Methods and Systems for Manufacturing and Heavy Industry applicationsData mining methods and systems for life science, biological applicationsData mining for medical informatics and health care applicationsData mining for environmental applications such as climate modelingData mining for emerging applications such as web mining, social network analysisData mining applications in other domains such as civil engineering, financial engineeringInvited SpeakerEamonn Keogh from University of California at Riverside, USAImportant DateSubmission deadline: TBDReview period: approximately 3 weeksNotification date: TBDFinal version submission date: TBDSubmissionsPlease prepare your paper not more than 10 pages in PDF file, with IEEE camera‐ready template: http://wi-lab.com/cyberchair/icdm09/scripts/submit.php
.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. If you cannot submit there, please send to us by email us.ibm.com>.Workshop Co-ChairsChid Apte, IBM TJ WatsonWray Buntine, Canberra Research LaboratoryYan Liu, IBM TJ WatsonJimeng Sun, IBM TJ WatsonJie Tang, Tsinghua UniversityProgram CommitteeAlex Gray, Geogia TechRayid Ghani, AccentureCharles Elkan, University of California, San DiegoJennifer Neville, Purdue UniversityMohammed Zaki, Rensselaer Polytechnic Institute Dong Zhang, Google Inc.Lei Zhang, Microsoft Research AsiaZhong Su, IBM, CRLXifeng Yan, University of California, San BabaraSpiros Papadimitriou, IBMTamara Kolda, Sandia National LabsPetros Drineas, RPIEdwin Pednault, IBM ResearchElad Yom-Tov, IBM ResearchPhilip S. Yu, University of Illinois at ChicagoQiang Yang, Hong Kong University of Science and TechnologyHuiming Qu, IBM TJ WatsonSanjay Chawla, University of SydneyYu-Ru Lin, ASUContact usYan Liu, IBM TJ Watson Research Center, liuya
us.ibm.com, 1-914-945-2128
Keywords: Accepted papers list. Acceptance Rate. EI Compendex. Engineering Index. ISTP index. ISI index. Impact Factor.
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