Fuzzy time series and its models
Fuzzy Sets and Systems
Fast subsequence matching in time-series databases
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
Efficiently supporting ad hoc queries in large datasets of time sequences
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Adaptive query processing for time-series data
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Efficient Similarity Search In Sequence Databases
FODO '93 Proceedings of the 4th International Conference on Foundations of Data Organization and Algorithms
An Online Algorithm for Segmenting Time Series
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Using Signature Files for Querying Time-Series Data
PKDD '97 Proceedings of the First European Symposium on Principles of Data Mining and Knowledge Discovery
Efficient Time Series Matching by Wavelets
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
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
Local feature extraction and its applications using a library of bases
Local feature extraction and its applications using a library of bases
Supervised classification with temporal data
Supervised classification with temporal data
Optimal Piecewise-Linear Approximation Algorithms for Complex Dependencies
Automation and Remote Control
Stylized facts of financial time series and hidden semi-Markov models
Computational Statistics & Data Analysis
Linearly constrained global optimization via piecewise-linear approximation
Journal of Computational and Applied Mathematics
Artificial Intelligence with Uncertainty
Artificial Intelligence with Uncertainty
Evolving and clustering fuzzy decision tree for financial time series data forecasting
Expert Systems with Applications: An International Journal
An Improvement of PAA for Dimensionality Reduction in Large Time Series Databases
PRICAI '08 Proceedings of the 10th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
Financial time-series analysis with rough sets
Applied Soft Computing
Implementing a data mining solution for enhancing carpet manufacturing productivity
Knowledge-Based Systems
Integration of genetic fuzzy systems and artificial neural networks for stock price forecasting
Knowledge-Based Systems
A review on time series data mining
Engineering Applications of Artificial Intelligence
Shape-based template matching for time series data
Knowledge-Based Systems
Hybrid method for the analysis of time series gene expression data
Knowledge-Based Systems
Short communication: Selective Subsequence Time Series clustering
Knowledge-Based Systems
Time series visualization based on shape features
Knowledge-Based Systems
Similarity search for time series based on efficient warping measure
DM-IKM '12 Proceedings of the Data Mining and Intelligent Knowledge Management Workshop
Finding time series discord based on bit representation clustering
Knowledge-Based Systems
Asynchronism-based principal component analysis for time series data mining
Expert Systems with Applications: An International Journal
HMM-based hybrid meta-clustering ensemble for temporal data
Knowledge-Based Systems
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Many researchers focus on dimensionality reduction techniques for the efficient data mining in large time series database. Meanwhile, corresponding distance measures are provided for describing the relationships between two different time series in reduced space. In this paper, we propose a novel approach which we call piecewise cloud approximation (PWCA) to reduce the dimensionality of time series. This representation not only allows dimensionality reduction but also gives a new way to measure the similarity between time series well. Cloud, a qualitative and quantitative transformation model, is used to describe the features of subsequences of time series. Furthermore, a new way to measure the similarity between two cloud models is defined by an overlapping area of their own expectation curves. We demonstrate the performance of the proposed representation and similarity measure used in time series mining tasks, including clustering, classification and similarity search. The results of experiments indicate that PWCA is an effective representation for time series mining.