Discovering the Longest Set of Distinct Maximal Correlated Intervals in Time Series Data
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Discovering the Longest Set of Distinct Maximal Correlated Intervals in Time Series Data
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2014-10-01
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In this paper we focus on finding all maximal correlated intervals where a given pair of time series have correlation above a user provided threshold for all its subintervals and for none of its immediate subsuming intervals. Our objective then is to find a longest set of such maximal correlated intervals. We propose a two step solution to achieve this objective. In the first step an efficient bottom-up approach is proposed to discover maximal correlated intervals. In the second step we use a dynamic programming approach to select the longest non-overlapping set. We evaluate the efficiency of our approach on synthetic datasets and compare it with that of a bruteforce approach. Using neuroimaging data that contains activity time series from brain regions, we show the utility of our approach in studying transient nature of relationships between different brain regions.
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Atluri, Gowtham; Steinbach, Michael; Lim, Kelvin; MacDonald, Angus; Kumar, Vipin. (2014). Discovering the Longest Set of Distinct Maximal Correlated Intervals in Time Series Data. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/215962.
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