Before revision: We give the first ANN-data structure for time series under the continuous Fr\'echet distance , where ANN stands for approximate near neighbor . Given a parameter \epsilon \in (0,1], the data structure can be used to preprocess n curves in Euclidean R (aka time series), each of complexity m, to answer queries with a curve of complexity k by either returning a curve that lies within Fr\'echet distance 2+\epsilon, or answering that there exists no curve in the input within distance 1.
After revision: We give the first approximate-near-neighbor data structure for time series under the continuous Fr\'echet distance , where ANN stands for approximate near neighbor . Given a parameter \epsilon \in (0,1], the data structure can be used to preprocess n curves in Euclidean R (aka time series), each of complexity m, to answer queries with a curve of complexity k by either returning a curve that lies within Fr\'echet distance 2+\epsilon, or answering that there exists no curve in the input within distance 1.