Journal of Algorithms
Readings in qualitative reasoning about physical systems
Readings in qualitative reasoning about physical systems
Fast subsequence matching in time-series databases
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
Distributed associative memories for high-speed symbolic reasoning
Fuzzy Sets and Systems - Special issue on connectionist and hybrid connectionist systems for approximate reasoning
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
CACTUS—clustering categorical data using summaries
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Deformable Markov model templates for time-series pattern matching
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Locally adaptive dimensionality reduction for indexing large time series databases
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Values
Data Mining and Knowledge Discovery
SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
Efficient Similarity Search In Sequence Databases
FODO '93 Proceedings of the 4th International Conference on Foundations of Data Organization and Algorithms
Fast Time Sequence Indexing for Arbitrary Lp Norms
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Mixtures of ARMA Models for Model-Based Time Series Clustering
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Efficient Time Series Matching by Wavelets
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
On the Need for Time Series Data Mining Benchmarks: A Survey and Empirical Demonstration
Data Mining and Knowledge Discovery
Warping indexes with envelope transforms for query by humming
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
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
Clustering binary data streams with K-means
DMKD '03 Proceedings of the 8th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery
A Comparison of Standard Spell Checking Algorithms and a Novel Binary Neural Approach
IEEE Transactions on Knowledge and Data Engineering
Probabilistic discovery of time series motifs
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Weather Data Mining Using Independent Component Analysis
The Journal of Machine Learning Research
Indexing spatio-temporal trajectories with Chebyshev polynomials
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
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
Exact indexing of dynamic time warping
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
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
Dimensionality reduction for long duration and complex spatio-temporal queries
Proceedings of the 2007 ACM symposium on Applied computing
iSAX: disk-aware mining and indexing of massive time series datasets
Data Mining and Knowledge Discovery
Anomaly detection in radiation sensor data with application to transportation security
IEEE Transactions on Intelligent Transportation Systems
Representing financial time series based on important extrema points
IITA'09 Proceedings of the 3rd international conference on Intelligent information technology application
Exact indexing for massive time series databases under time warping distance
Data Mining and Knowledge Discovery
Shape pattern matching: A tool to cluster unstructured text documents
Journal of Computational Methods in Sciences and Engineering - Special Supplement Issue in Section A and B: Selected Papers from the ISCA International Conference on Software Engineering and Data Engineering, 2009
Efficient algorithm for a novel pattern of time series
Expert Systems with Applications: An International Journal
A review on time series data mining
Engineering Applications of Artificial Intelligence
A novel clustering method on time series data
Expert Systems with Applications: An International Journal
How many reference patterns can improve profitability for real-time trading in futures market?
Expert Systems with Applications: An International Journal
Small gestures go a long way: how many bits per gesture do recognizers actually need?
Proceedings of the Designing Interactive Systems Conference
Model-based integration of past & future in TimeTravel
Proceedings of the VLDB Endowment
ACM Computing Surveys (CSUR)
STFMap: query- and feature-driven visualization of large time series data sets
Proceedings of the 21st ACM international conference on Information and knowledge management
The impact of motion dimensionality and bit cardinality on the design of 3D gesture recognizers
International Journal of Human-Computer Studies
Finding time series discord based on bit representation clustering
Knowledge-Based Systems
An approach to dimensionality reduction in time series
Information Sciences: an International Journal
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Clipping is the process of transforming a real valued series into a sequence of bits representing whether each data is above or below the average. In this paper, we argue that clipping is a useful and flexible transformation for the exploratory analysis of large time dependent data sets. We demonstrate how time series stored as bits can be very efficiently compressed and manipulated and that, under some assumptions, the discriminatory power with clipped series is asymptotically equivalent to that achieved with the raw data. Unlike other transformations, clipped series can be compared directly to the raw data series. We show that this means we can form a tight lower bounding metric for Euclidean and Dynamic Time Warping distance and hence efficiently query by content. Clipped data can be used in conjunction with a host of algorithms and statistical tests that naturally follow from the binary nature of the data. A series of experiments illustrate how clipped series can be used in increasingly complex ways to achieve better results than other popular representations. The usefulness of the proposed representation is demonstrated by the fact that the results with clipped data are consistently better than those achieved with a Wavelet or Discrete Fourier Transformation at the same compression ratio for both clustering and query by content. The flexibility of the representation is shown by the fact that we can take advantage of a variable Run Length Encoding of clipped series to define an approximation of the Kolmogorov complexity and hence perform Kolmogorov based clustering.