  Traditional approaches focus on finding relationships between two entire time
series, however, many interesting relationships exist in small sub-intervals of
time and remain feeble during other sub-intervals. We define the notion of a
sub-interval relationship (SIR) to capture such interactions that are prominent
only in certain sub-intervals of time. To that end, we propose a fast-optimal
guaranteed algorithm to find most interesting SIR relationship in a pair of
time series. Lastly, we demonstrate the utility of our method in climate
science domain based on a real-world dataset along with its scalability scope
and obtain useful domain insights.
