Title
StreamAR: Incremental and Active Learning with Evolving Sensory Data for Activity Recognition
Abstract
Activity recognition focuses on inferring current user activities by leveraging sensory data available on todayÕs sensor rich environment. Supervised learning has been applied pervasively for activity recognition. Typical activity recognition techniques process sensory data based on point-by-point approaches. In this paper, we propose a novel cluster-based classification for activity recognition Systems, termed StreamAR. The system incorporates incremental and active learning for mining user activities in data streams. The novel approach processes activities as clusters to build a robust classification framework. StreamAR integrates supervised, unsupervised and active learning and applies hybrid similarity measures technique for recognising activities. Extensive experimental results using real activity recognition datasets have evidenced that our new approach shows improved performance over other existing state-of-the-art learning methods.
Year
DOI
Venue
2012
10.1109/ICTAI.2012.169
ICTAI), 2012 IEEE 24th International Conference
Keywords
Field
DocType
data mining,pattern classification,ubiquitous computing,unsupervised learning,StreamAR,active learning,activity recognition system,cluster-based classification,data streams,incremental learning,real activity recognition datasets,robust classification framework,sensory data,sensory data processing,supervised learning,unsupervised learning,user activity mining,activity recognition,sensory data,stream mining
Data modeling,Data mining,Data stream mining,Semi-supervised learning,Computer science,Unsupervised learning,Artificial intelligence,Cluster analysis,Activity recognition,Active learning,Pattern recognition,Supervised learning,Machine learning
Conference
Volume
ISSN
ISBN
1
1082-3409
978-1-4799-0227-9
Citations 
PageRank 
References 
16
0.64
13
Authors
4
Name
Order
Citations
PageRank
Zahraa Said Abdallah1886.20
Mohamed Medhat Gaber2201.70
Bala Srinivasan3160.64
Shonali Krishnaswamy4211.49