Introduction to algorithms
Real-Time American Sign Language Recognition Using Desk and Wearable Computer Based Video
IEEE Transactions on Pattern Analysis and Machine Intelligence
PERUSE: An Unsupervised Algorithm for Finding Recurrig Patterns in Time Series
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
A symbolic representation of time series, with implications for streaming algorithms
DMKD '03 Proceedings of the 8th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery
Probabilistic discovery of time series motifs
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Towards parameter-free data mining
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
A generic motif discovery algorithm for sequential data
Bioinformatics
Discovering frequent work procedures from resource connections
Proceedings of the 14th international conference on Intelligent user interfaces
Discovering multivariate motifs using subsequence density estimation and greedy mixture learning
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Proceedings of the 2008 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
Toward unsupervised activity discovery using multi-dimensional motif detection in time series
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
On the use of magnetic field disturbances as features for activity recognition with on body sensors
EuroSSC'10 Proceedings of the 5th European conference on Smart sensing and context
Unsupervised discovery of motifs under amplitude scaling and shifting in time series databases
MLDM'11 Proceedings of the 7th international conference on Machine learning and data mining in pattern recognition
Accelerometer-based on-body sensor localization for health and medical monitoring applications
Pervasive and Mobile Computing
Significant motifs in time series
Statistical Analysis 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
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A fundamental problem for artificial intelligence is identifying perceptual primitives from raw sensory signals that are useful for higher-level reasoning. We equate these primitives with initially unknown recurring patterns called motifs. Autonomously learning the motifs is difficult because their number, location, length, and shape are all unknown. Furthermore, nonlinear temporal warping may be required to ensure the similarity of motif occurrences. In this paper, we extend a leading motif discovery algorithm by allowing it to operate on multidimensional sensor data, incorporating automatic parameter estimation, and providing for motif-specific similarity adaptation. We evaluate our algorithm on several data sets and show how our approach leads to faster real world discovery and more accurate motifs compared to other leading methods.