Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
MobiMine: monitoring the stock market from a PDA
ACM SIGKDD Explorations Newsletter
Adapting Applications in Mobile Terminals Using Fuzzy Context Information
Mobile HCI '02 Proceedings of the 4th International Symposium on Mobile Human-Computer Interaction
Towards a Theory of Context Spaces
PERCOMW '04 Proceedings of the Second IEEE Annual Conference on Pervasive Computing and Communications Workshops
Reasoning about Uncertain Contexts in Pervasive Computing Environments
IEEE Pervasive Computing
Rule Based Expert Systems: The Mycin Experiments of the Stanford Heuristic Programming Project (The Addison-Wesley series in artificial intelligence)
Service Adaptation Using Fuzzy Theory in Context-Aware Mobile Computing Middleware
RTCSA '05 Proceedings of the 11th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications
An Adaptive Middleware Infrastructure Incorporating Fuzzy Logic for Mobile Computing
NWESP '05 Proceedings of the International Conference on Next Generation Web Services Practices
In-Network Data Processing forWireless Sensor Networks
MDM '06 Proceedings of the 7th International Conference on Mobile Data Management
Situational computing: An innovative architecture with imprecise reasoning
Journal of Systems and Software
An approach to data fusion for context awareness
CONTEXT'05 Proceedings of the 5th international conference on Modeling and Using Context
Self-configuring data mining for ubiquitous computing
Information Sciences: an International Journal
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In resource-constrained devices, adaptation of data stream processing to variations of data rates and availability of resources is crucial for consistency and continuity of running applications. However, to enhance and maximize the benefits of adaptation, there is a need to go beyond mere computational and device capabilities to encompass the full spectrum of context-awareness. This paper presents a general approach for context-aware adaptive mining of data streams that aims to dynamically and autonomously adjust data stream mining parameters according to changes in context and situations. We perform intelligent and real-time analysis of data streams generated from sensors that is under-pinned using context-aware adaptation. A prototype of the proposed architecture is implemented and evaluated in the paper through a real-world scenario in the area of healthcare monitoring.