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• W2965708114 abstract "This paper studies the r-range search problem for curves under the continuous Frechet distance: given a dataset S of n polygonal curves and a threshold (r>0), construct a data structure that, for any query curve q, efficiently returns all entries in S with distance at most r from q. We propose FRESH, an approximate and randomized approach for r-range search, that leverages on a locality sensitive hashing scheme for detecting candidate near neighbors of the query curve, and on a subsequent pruning step based on a cascade of curve simplifications. We experimentally compare FRESH to exact and deterministic solutions, and we show that high performance can be reached by suitably relaxing precision and recall." @default.
• W2965708114 created "2019-08-13" @default.
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• W2965708114 date "2019-01-01" @default.
• W2965708114 modified "2023-09-23" @default.
• W2965708114 title "FRESH: Fréchet Similarity with Hashing" @default.
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• W2965708114 doi "https://doi.org/10.1007/978-3-030-24766-9_19" @default.
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