Algorithms for clustering data
Algorithms for clustering data
Fast and effective text mining using linear-time document clustering
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Trajectory clustering with mixtures of regression models
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
A general probabilistic framework for clustering individuals and objects
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
A Bayesian Approach to Temporal Data Clustering using Hidden Markov Models
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Using Dynamic Time Warping to Bootstrap HMM-Based Clustering of Time Series
Sequence Learning - Paradigms, Algorithms, and Applications
A Method for Clustering the Experiences of a Mobile Robot that Accords with Human Judgments
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
On the need for time series data mining benchmarks: a survey and empirical demonstration
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Mixtures of ARMA Models for Model-Based Time Series Clustering
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Where is . •.? learning and utilizing motion patterns of persons with mobile robots
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Discovering clusters in motion time-series data
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Learning action models from plan examples using weighted MAX-SAT
Artificial Intelligence
Spectral Clustering and Embedding with Hidden Markov Models
ECML '07 Proceedings of the 18th European conference on Machine Learning
A new distance measure for hidden Markov models
Expert Systems with Applications: An International Journal
Audio query by example using similarity measures between probability density functions of features
EURASIP Journal on Audio, Speech, and Music Processing - Special issue on scalable audio-content analysis
Machine learning approaches for time-series data based on self-organizing incremental neural network
ICANN'10 Proceedings of the 20th international conference on Artificial neural networks: Part III
A review on time series data mining
Engineering Applications of Artificial Intelligence
State-space dynamics distance for clustering sequential data
Pattern Recognition
Unsupervised categorization of human motion sequences
Intelligent Data Analysis
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We present a novel approach for clustering sequences of multi-dimensional trajectory data obtained from a sensor network. The sensory time-series data present new challenges to data mining, including uneven sequence lengths, multi-dimensionality and high levels of noise. We adopt a principled approach, by first transforming all the data into an equal-length vector form while keeping as much temporal information as we can, and then applying dimensionality and noise reduction techniques such as spectral clustering to the transformed data. Experimental evaluation on synthetic and real data shows that our proposed approach outperforms standard model-based clustering algorithms for time series data.