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
On the Need for Time Series Data Mining Benchmarks: A Survey and Empirical Demonstration
Data Mining and Knowledge Discovery
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
A unified framework for model-based clustering
The Journal of Machine Learning Research
Clustering time series from ARMA models with clipped data
Proceedings of the tenth 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
Clustering Time Series with Clipped Data
Machine Learning
A Multiresolution Symbolic Representation of Time Series
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
MSR '05 Proceedings of the 2005 international workshop on Mining software repositories
Structural Periodic Measures for Time-Series Data
Data Mining and Knowledge Discovery
Time-focused clustering of trajectories of moving objects
Journal of Intelligent Information Systems
Compression-based data mining of sequential data
Data Mining and Knowledge Discovery
Clustering data with measurement errors
Computational Statistics & Data Analysis
Experiencing SAX: a novel symbolic representation of time series
Data Mining and Knowledge Discovery
Time series clustering and classification by the autoregressive metric
Computational Statistics & Data Analysis
Efficient Similarity Search over Future Stream Time Series
IEEE Transactions on Knowledge and Data Engineering
Clustering of biological time series by cepstral coefficients based distances
Pattern Recognition
International Journal of Network Management
Efficient discovery of unusual patterns in time series
New Generation Computing
Time series analysis with multiple resolutions
Information Systems
BioMED '08 Proceedings of the Sixth IASTED International Conference on Biomedical Engineering
Clustering of time series data-a survey
Pattern Recognition
MLDM'03 Proceedings of the 3rd international conference on Machine learning and data mining in pattern recognition
A novel two-level clustering method for time series data analysis
Expert Systems with Applications: An International Journal
Clustering of vehicle trajectories
IEEE Transactions on Intelligent Transportation Systems
A review on time series data mining
Engineering Applications of Artificial Intelligence
Parsimonious linear fingerprinting for time series
Proceedings of the VLDB Endowment
Fuzzy clustering of time series in the frequency domain
Information Sciences: an International Journal
A novel clustering method on time series data
Expert Systems with Applications: An International Journal
An IFS-based similarity measure to index electroencephalograms
PAKDD'11 Proceedings of the 15th Pacific-Asia conference on Advances in knowledge discovery and data mining - Volume Part II
Learning actions in complex software systems
DaWaK'11 Proceedings of the 13th international conference on Data warehousing and knowledge discovery
Wireless sensor network system for supporting nursing context-awareness
International Journal of Autonomous and Adaptive Communications Systems
Stock time series categorization and clustering via SB-Tree optimization
FSKD'06 Proceedings of the Third international conference on Fuzzy Systems and Knowledge Discovery
Classifying motion time series using neural networks
PCM'06 Proceedings of the 7th Pacific Rim conference on Advances in Multimedia Information Processing
Wavelets-based clustering of multivariate time series
Fuzzy Sets and Systems
A likelihood ratio distance measure for the similarity between the fourier transform of time series
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
A BIRCH-Based clustering method for large time series databases
PAKDD'11 Proceedings of the 15th international conference on New Frontiers in Applied Data Mining
ISAAC'11 Proceedings of the 22nd international conference on Algorithms and Computation
ACM Computing Surveys (CSUR)
Feature selection for classification of oscillating time series
Expert Systems: The Journal of Knowledge Engineering
Large margin mixture of AR models for time series classification
Applied Soft Computing
A hypothesis test using bias-adjusted AR estimators for classifying time series in small samples
Computational Statistics & Data Analysis
Computational Geometry: Theory and Applications
Polarization of forecast densities: A new approach to time series classification
Computational Statistics & Data Analysis
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Many environmental and socioeconomic time-series data can be adequately modeled using Auto-RegressiveIntegrated Moving Average (ARIMA) models. We call such Time-series ARIMA time-series. We consider the problem of clustering ARIMA time-series. We propose the use of the Linear Predictive Coding (LPC) cepstrum of time-series for clustering ARIMA time-series, by using the Euclideandistance between the LPC cepstra of two time-series as their dissimilarity measure. We demonstrate that LPC cepstral coefficients have the desire features for accurate clustering and efficient indexing of ARIMA time-series. For example, few LPC cepstral coefficients are sufficient in order todiscriminate between time-series that are modeled by different ARIMA models. In fact this approach requires fewer coefficients than traditional approaches, such as DFT and DWT. The proposed distance measure can be use for measuring the similarity between different ARIMA models as well.We cluster ARIMA time-series using the Partition Around Medoids method with various similarity measures. We present experimental results demonstrating that using the proposed measure we achieve significantly betterclusterings of ARIMA time-series data as compared to clusterings obtained by using other traditional similaritymeasures, such as DFT, DWT, PCA, etc. Experiments wereperformed both on simulated as well as real data.