Locally adaptive dimensionality reduction for indexing large time series databases
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Hyper-rectangle based segmentation and clustering of large video data sets
Information Sciences—Informatics and Computer Science: An International Journal - Special issue: Intelligent multimedia computing and networking
Fast Time Sequence Indexing for Arbitrary Lp Norms
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
A Signature Technique for Similarity-Based Queries
SEQUENCES '97 Proceedings of the Compression and Complexity of Sequences 1997
Supporting Content-Based Searches on Time Series via Approximation
SSDBM '00 Proceedings of the 12th International Conference on Scientific and Statistical Database Management
Similarity Search for Multidimensional Data Sequences
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Waveform Segmentation Through Functional Approximation
IEEE Transactions on Computers
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In this paper we present an effective pattern similarity match algorithm for multidimensional sequence data sets such as video streams and various analog or digital signals. To approximate a sequence of data points we introduce a trend vectorthat captures the moving trend of the sequence. Using the trend vector, our method is designed to filter out irrelevant sequences from a database and to find similar sequences with respect to a query. Experimental results show that it provides a lower reconstruction error and a higher precision rate compared to existing methods.