Adaptive mobile activity recognition system with evolving data streams

Mobile activity recognition focuses on inferring current user activities by leveraging sensory data available on today׳s sensor rich mobile phones. Supervised learning with static models has been applied pervasively for mobile activity recognition. In this paper, we propose a novel phone-based dynam...

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Bibliographic Details
Published in:	Neurocomputing (Amsterdam) Vol. 150; pp. 304 - 317
Main Authors:	Abdallah, Zahraa Said, Gaber, Mohamed Medhat, Srinivasan, Bala, Krishnaswamy, Shonali
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 20.02.2015
Subjects:	Active learning Activity recognition Data transmission Dynamical systems Dynamics Evolution Incremental learning Learning Mobile application Real time Recognition Stream mining Streams Ubiquitous computing Activity recognition Ubiquitous computing Incremental learning Mobile application Stream mining Active learning
ISSN:	0925-2312, 1872-8286
Online Access:	Get full text
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