AwareCast 2014

New Call for Papers!

Please note, we have an updated Call for Papers online.

Topics

Context prediction breaks the border from reaction on past and present stimuli to proactive anticipation of actions. Research directions spread from applications for context prediction over event prediction, architectures for context prediction, data formats, and algorithms. Recent work focuses on three main challenges:

Prediction beyond location
Benchmarks and common data sets
Common development frameworks

While there have been contributions targeting some of these challenges, we still see them as unsolved. Thus we invite unique contribution addressing these challenges and provide a forum to facilitate collaboration among research groups focusing on context prediction.

Topics of interest include, but are not limited to:

Accurate prediction of seldom events

Important events are frequently also seldom events. How can we train a system on events which are not likely covered by training data sets?

Identification of actions and situations suitable for context prediction

User behavior is noisy and not necessarily contains patterns, which can be predicted. In particular, predictable patterns are frequently interleaved with non-predictable patterns. Inherently, the underlying (stochastic?) process has to feature some regularity or trends.

Continuous learning

User behavior and habit changes over time. To guarantee constant accuracy, the approach must be able to ‘forget’ patterns which grow unimportant.

Development frameworks

To pave the way for a broader use of context prediction in applications, robust and easy to use frameworks are in need. These frameworks should simplify the development of context prediction applications and preferably be available as open source.

Novel applications

As discussed above, research on context prediction used to focus heavily on location prediction. While contributions dealing with location prediction are welcome, when they address at least one of the other topics, we like to see novel application of context prediction.

Multi-User and Multi-Sensor Prediction

Since humans tend to behave similar, context time series of other users may be helpful to increase the accuracy of context prediction for similar users. Additionally the utilization of multiple sensors may affect the robustness of the prediction approaches.

Data sets and benchmarks

Currently, comprehensive data-sets are created for context-computing. However, these data-sets are hardly sufficient to be applied for context prediction applications. In particular, data has to be sampled over longer time-spans and cover stochastic processes which are inherently predictable.

Privacy and trust

Shared time series but also the fact that context time series might cover events and actions of remote entities rises questions of privacy and trust.

Data properties and metrics

Context data may have properties leveraging context prediction, e.g. periodicity of predictable patterns. How can properties of context data be generalized? Which properties make data suitable for context prediction, and which properties don’t? Can we define metrics to measure data properties?

Technical Program

Technical Program ...

Attending

Registration is managed by the Ubicomp 2014 registration chair. More ...

Program Committee (preliminary)

Christos Anagnostopoulos, Ionian University
Martin Atzmueller, University of Kassel
Dirk Bade, University of Hamburg
Sebastian Bader, Rostock University
Michael Beigl, KIT
Diane Cook, Washington State University
Tristan Henderson, University of St Andrews
Sian Lun Lau, Sunway University, Malaysia
Teddy Mantoro, Universitas Siswa Bangsa International, Jakarta
Mirco Musolesi, University of Birmingham
Andrei Popleteev, Create-Net
Till Riedel, KIT
Andreas Riener, Johannes Kepler University Linz
Nirmalya Roy, Washington State University
Kristof Van Laerhoven, TU Darmstadt
Sebastian VanSyckel, University of Mannheim
Arkady Zaslavsky, CSIRO
Mi Zhang, Cornell University

Important Dates

Extended Paper Submission Deadline: May 27, 2014
Author Notification: June 18, 2014
Camera-ready version due: July 03, 2014
Workshop: September 14, 2014

Submission Instructions

Template: SIGCHI Extended Abstract (Word | LaTeX)
Page limit: 10 pages
Submission: via EasyChair.
All accepted submissions must be presented at the AwareCast 2014 workshop.

UbiComp 2014

The 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2014) is the result of a merger of the two most renown conferences in the field: Pervasive and UbiComp. More ...

Workshop Chairs

Klaus David, Kassel University, Germany
Rico Kusber, Kassel University, Germany
Sian Lun Lau, Sunway University, Malaysia
Stephan Sigg, Georg-August University Goettingen, Germany
Brian Ziebart, University of Illinois at Chicago, USA

Past Events

AwareCast 2013
AwareCast 2012