Fast subsequence matching in time-series databases
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
An introduction to Kolmogorov complexity and its applications (2nd ed.)
An introduction to Kolmogorov complexity and its applications (2nd ed.)
Deformable Markov model templates for time-series pattern matching
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining the stock market (extended abstract): which measure is best?
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
A vector space model for automatic indexing
Communications of the ACM
Locally adaptive dimensionality reduction for indexing large time series databases
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Efficient Similarity Search In Sequence Databases
FODO '93 Proceedings of the 4th International Conference on Foundations of Data Organization and Algorithms
Pattern Extraction for Time Series Classification
PKDD '01 Proceedings of the 5th European Conference on Principles of Data Mining and Knowledge Discovery
Feature-based classification of time-series data
Information processing and technology
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
Learning to Recognize Time Series: Combining ARMA models with memory-based learning
CIRA '97 Proceedings of the 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation
Efficient Time Series Matching by Wavelets
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Towards parameter-free data mining
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Characteristic-Based Clustering for Time Series Data
Data Mining and Knowledge Discovery
Finding the most unusual time series subsequence: algorithms and applications
Knowledge and Information Systems
Experiencing SAX: a novel symbolic representation of time series
Data Mining and Knowledge Discovery
Exact indexing of dynamic time warping
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
A review on time series data mining
Engineering Applications of Artificial Intelligence
A method of similarity measure and visualization for long time series using binary patterns
PAKDD'11 Proceedings of the 15th international conference on New Frontiers in Applied Data Mining
ACM Computing Surveys (CSUR)
Rotation-invariant similarity in time series using bag-of-patterns representation
Journal of Intelligent Information Systems
Motif discovery in spatial trajectories using grammar inference
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
HMM-based hybrid meta-clustering ensemble for temporal data
Knowledge-Based Systems
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For more than one decade, time series similarity search has been given a great deal of attention by data mining researchers. As a result, many time series representations and distance measures have been proposed. However, most existing work on time series similarity search focuses on finding shape-based similarity. While some of the existing approaches work well for short time series data, they typically fail to produce satisfactory results when the sequence is long. For long sequences, it is more appropriate to consider the similarity based on the higher-level structures. In this work, we present a histogram-based representation for time series data, similar to the "bag of words" approach that is widely accepted by the text mining and information retrieval communities. We show that our approach outperforms the existing methods in clustering, classification, and anomaly detection on several real datasets.