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Data structures for detecting rare variations in time series

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2012) 7524 LNAI(PART 2) 709-724
DOI: 10.1007/978-3-642-33486-3_45
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Abstract

In this paper we study, from both a theoretical and an experimental perspective, algorithms and data structures to process queries that help in the detection of rare variations over time intervals that occur in time series. Our research is strongly motivated by applications in financial domain. © 2012 Springer-Verlag.

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Valentim, C., Laber, E. S., & Sotelo, D. (2012). Data structures for detecting rare variations in time series. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7524 LNAI, pp. 709–724). https://doi.org/10.1007/978-3-642-33486-3_45

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