Activity recognition via user-trace segmentation
ACM Transactions on Sensor Networks (TOSN)
Mining fuzzy frequent trends from time series
Expert Systems with Applications: An International Journal
A novel sequence representation for unsupervised analysis of human activities
Artificial Intelligence
Activity recognition through goal-based segmentation
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
Discovering multivariate motifs using subsequence density estimation and greedy mixture learning
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Improving activity discovery with automatic neighborhood estimation
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Proceedings of the 2008 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
A tree-construction search approach for multivariate time series motifs discovery
Pattern Recognition Letters
Approximate variable-length time series motif discovery using grammar inference
Proceedings of the Tenth International Workshop on Multimedia Data Mining
Lag patterns in time series databases
DEXA'10 Proceedings of the 21st international conference on Database and expert systems applications: Part II
Discovering deformable motifs in continuous time series data
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
Significant motifs in time series
Statistical Analysis and Data Mining
Testing the significance of spatio-temporal teleconnection patterns
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
CPMD: a matlab toolbox for change point and constrained motif discovery
IEA/AIE'12 Proceedings of the 25th international conference on Industrial Engineering and Other Applications of Applied Intelligent Systems: advanced research in applied artificial intelligence
G-SteX: greedy stem extension for free-length constrained motif discovery
IEA/AIE'12 Proceedings of the 25th international conference on Industrial Engineering and Other Applications of Applied Intelligent Systems: advanced research in applied artificial intelligence
Finding recurrent patterns from continuous sign language sentences for automated extraction of signs
The Journal of Machine Learning Research
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This paper describes PERUSE, an unsupervised algorithm for finding recurring patterns in time series.It was initially developed and tested with sensor data from a mobile robot, i.e. noisy, re-valued, multivariate time series with variable intervals between observations.The pattern discovery problem is decomposed into two sub-problems: (1) a supervised learning problem in which a teacher provised exemplars of patterns and labels time series according to whether they contain the patterns; (2)an un supervised learning problem in which the time series are used to generate an approximation to the teacher.Experimental results show that PERUSE can discover patterns in audio data corresponding to qualitatively distinct outcomes of taking actions.