Fundamentals of speech recognition
Fundamentals of speech recognition
Fast subsequence matching in time-series databases
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
Finding patterns in time series: a dynamic programming approach
Advances in knowledge discovery and data mining
Fast Similarity Search in the Presence of Noise, Scaling, and Translation in Time-Series Databases
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Similarity Search Over Time-Series Data Using Wavelets
ICDE '02 Proceedings of the 18th 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
Visually mining and monitoring massive time series
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
HOT SAX: Efficiently Finding the Most Unusual Time Series Subsequence
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
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
VizTree: a tool for visually mining and monitoring massive time series databases
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
A performance comparison of piecewise linear estimation methods
Proceedings of the 2008 Spring simulation multiconference
Stock time series visualization based on data point importance
Engineering Applications of Artificial Intelligence
Pattern Recognition, Fourth Edition
Pattern Recognition, Fourth Edition
Finding Structural Similarity in Time Series Data Using Bag-of-Patterns Representation
SSDBM 2009 Proceedings of the 21st International Conference on Scientific and Statistical Database Management
In-depth behavior understanding and use: The behavior informatics approach
Information Sciences: an International Journal
Time series visualization based on shape features
Knowledge-Based Systems
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Similarity measure and visualization are two of the most interesting tasks in time series data mining and attract much attention in the last decade. Some representations have been proposed to reduce high dimensionality of time series and the corresponding distance functions have been used to measure their similarity. Moreover, visualization techniques are often based on such representations. One of the most popular time series visualization is time series bitmaps using chaos-game algorithm. In this paper, we propose an alternative version of the long time series bitmaps of which the number of the alphabets is not restricted to four. Simultaneously, the corresponding distance function is also proposed to measure the similarity between long time series. Our approach transforms long time series into SAX symbolic strings and constructs a non-sparse matrix which stores the frequency of binary patterns. The matrix can be used to calculate the similarity and visualize the long time series. The experiments demonstrate that our approach not only can measure the long time series as well as the "bag of pattern" (BOP), but also can obtain better visual effects of the long time series visualization than the chaos-game based time series bitmaps (CGB). Especially, the computation cost of pattern matrix construction in our approach is lower than that in CGB.