================================================================== CALL FOR PAPERS
Workshop on recent advances in behavior prediction and pro-active pervasive computing (AwareCast) (http://www.ibr.cs.tu-bs.de/dus/Awarecast/) in conjunction with the 10th International Conference on Pervasive Computing (Pervasive 2012) (http://pervasiveconference.org/2012/) in Newcastle, UK, June 19th, 2012 ================================================================== Important dates Paper submission: March 14, 2012 [Extended] Notification of acceptance: April 06, 2012 [Extended] Camera Ready submission: April 20, 2012 Workshop: June 19, 2012 Scope Behavior and context prediction breaks the border from reaction on past and present stimuli to proactive anticipation of actions. Researchers have for about one decade now considered the prediction of such stimuli to enable pro-active context computing. Research directions spread from applications for behavior and context prediction over event prediction, information retrieval, machine learning, architectures for context prediction, data formats and algorithms. Even though a great diversity of applications for behavior and context prediction has been proposed, a common methodology or platform has not yet crystallised. Application developers are forced to start from scratch since previous authors seldom provided usable sources of their applications that could be extended. To foster the integration into applications, support for application developers has to be improved. We require a widely accepted architecture and toolkit - easy to use; with an open API; comprising common algorithms, accepted data sets and benchmarks. It should enable researchers to test prediction algorithms in a common environment on accepted data sets as well as to extend and import it by own algorithms and data sets. When it comes to algorithms for context prediction, a comprehensive comparison of strengths and weaknesses on benchmark data sets is yet missing. The motivation for choosing an algorithm for a specific application is not seldom driven by the experience and education of the researcher. Therefore, inherent properties such as the structure and requirements of the data as well as the application regarding accuracy and processing load are ignored. To raise the field to a level at which it might be integrated in commercial applications, common, widely accepted data sets need to be established as well as accepted benchmarks. Analytic studies mainly consider the computational complexity of time-series forecasting methods. They are required to establish a theoretically sound background for applications. Data formats or impacts of the restriction to few symbolical formats might foster comprehension of basic issues for prediction. Additionally, the computational complexity and the ability to distribute computational load among nodes in a network are promising research directions in order to enable prediction in systems of distributed, resource limited nodes. Promising ideas, broadening the field have been mentioned but are addressed superficially. A prominent example is prediction sharing among nodes in proximity. Related questions regard privacy and trust, service quality, communication and storage cost and accuracy amplification through redundancy. Likewise, the sharing of time series might be utilised for correction of measurement errors or predictions. Also, authors seldom address the prediction of rare events. In particular, for disaster or accident prevention, we would like to prevent extremely unlikely events for which possibly no training data exists. After about one decade of activities in the field of behavior and context prediction, the workshop will bring together researchers of this field and reveal important open issues. Among these are - Accurate prediction of seldom events - Continuous learning - User behaviour and habit changes over time - Prediction in public spaces - Machine learning - Information Retrieval - Creation and dissemination of data sets and benchmarks for pro-active computing and context prediction - Sharing of prediction and time series - Privacy and trust - Context prediction - Pattern matching and statistical approaches - Prediction of low level vs. high level context - User routine - Location, presence, availability, situation and action prediction - Proactive resource management - Algorithms for context prediction and time series forecasting - Event prediction - Accuracy of prediction methods - Computational complexity of prediction algorithms - Novel application areas, including applications for sustainability - Privacy preserving prediction approaches - Crowd sourcing for collaborative context prediction We are seeking unpublished and original submissions in PDF format. Papers must not exceed 12 pages formatted according to the LNCS format. Papers will be rigorously reviewed by an international technical program committee. Submissions will be evaluated on the basis of originality, significance of the contribution to the field, technical correctness and presentation. If a submitted paper overlaps in content with previously published or simultaneously reviewed work, the paper should make explicit how the work offers unique and substantial contribution beyond what has already been published or submitted. Accepted submissions will be published in the Pervasive 2012 Workshop Proceedings. Workshop organizers Niklas Klein, Kassel University, Kassel, Germany Stephan Sigg, National Institute of Informatics, Tokyo, Japan Brian Ziebart, Carnegie Mellon University, Pittsburgh, US Program Committee Christos Anagnostopoulos, Ionian University, Greece Martin Atzmueller, Kassel University, Germany Sebastian Bader, Rostock University, Germany Christian Becker, University of Mannheim, Germany Oliver Brdiczka, PARC, US Michael Beigl, Karlsruhe Institute of Technology, Germany Licia Capra, University College of London, UK Diane J. Cook, Washington State University, US Klaus David, Kassel University, Germany Anind Dey, Carnegie Mellon University, US Haym Hirsh, Rutgers University, US Winfried Lamersdorf, University of Hamburg, Germany Kun Chang Lee, Sungkyunkwan University, Korea Teddy Mantoro, KICT-IIUM, Malaysia Mirco Musolesi, University of Birmingham, UK Andrei Popleteev, Create-Net, Italy Andreas Riener, Johannes Kepler University Linz, Austria Nirmalya Roy, Institute for Infocomm Research (I2R), Singapore Kristof van Laerhoven, TU Darmstadt, Germany Sang Min Yoon, Yonsei University, Korea Arkady Zaslavsky, CSIRO ICT Centre, Australia Mi Zhang, University of Southern California, US
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