2 research outputs found
A Human-Centric Approach to Group-Based Context-Awareness
The emerging need for qualitative approaches in context-aware information
processing calls for proper modeling of context information and efficient
handling of its inherent uncertainty resulted from human interpretation and
usage. Many of the current approaches to context-awareness either lack a solid
theoretical basis for modeling or ignore important requirements such as
modularity, high-order uncertainty management and group-based
context-awareness. Therefore, their real-world application and extendability
remains limited. In this paper, we present f-Context as a service-based
context-awareness framework, based on language-action perspective (LAP) theory
for modeling. Then we identify some of the complex, informational parts of
context which contain high-order uncertainties due to differences between
members of the group in defining them. An agent-based perceptual computer
architecture is proposed for implementing f-Context that uses computing with
words (CWW) for handling uncertainty. The feasibility of f-Context is analyzed
using a realistic scenario involving a group of mobile users. We believe that
the proposed approach can open the door to future research on context-awareness
by offering a theoretical foundation based on human communication, and a
service-based layered architecture which exploits CWW for context-aware,
group-based and platform-independent access to information systems