Context-aware adaptive data stream mining

P. Haghighi, A. Zaslavsky, S. Krishnaswamy, M. Gaber, S. Loke

Research output: Contribution to journalArticlepeer-review

96 Downloads (Pure)

Abstract

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.
Original languageEnglish
Pages (from-to)423-434
Number of pages12
JournalIntelligent Data Analysis - Knowledge Discovery from Data Streams
Volume13
Issue number3
Publication statusPublished - 2009

Fingerprint

Dive into the research topics of 'Context-aware adaptive data stream mining'. Together they form a unique fingerprint.

Cite this