Integrating Data Mining into Feedback Loops for Predictive Context Adaptation
Date
2013-11-29
Authors
Rook, Angela
Knauss, Alessia
Damian, Daniela
Muller, Hausi A.
Thomo, Alex
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Abstract
Requirements for today's systems are increasingly
valid only within certain operating contexts.
Requirements engineering and implementation
stages of system development must
carefully consider how to integrate evolving
context related to specific requirements in order
for the system to stay relevant and
flexible.
In this paper we propose to use data mining
techniques for predictive context adaptation.
Our approach leverages data collected from the
past and decides, based on this historical data,
which context conditions to monitor in order
to predictively identify when a system needs to
be adapted to fulfill a particular requirement.
We demonstrate our approach on an adaptive
mobile application to support the coordination
of a team of rowers in an environment with a
continually changing operational context.