Abstract
The method of objects probabilistic search is developed based on the necessary proximity conditions in a Euclidean space, which were previously proved for the Levenshtein’s metric. The method is based on a random selection of k pivots in Euclidean space among the original objects, projecting all source objects in a k-dimensional Euclidean space, filling special hash data structures, and fast search facilities, similar to the desired, based on proven necessary conditions for the objects proximity in Euclidean space. Experimental studies of the proposed method show the higher speed in comparison with the known method.
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Chukhray, A., Havrylenko, O. (2020). Proximate Objects Probabilistic Searching Method. In: Nechyporuk, M., Pavlikov, V., Kritskiy, D. (eds) Integrated Computer Technologies in Mechanical Engineering. Advances in Intelligent Systems and Computing, vol 1113. Springer, Cham. https://doi.org/10.1007/978-3-030-37618-5_20
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DOI: https://doi.org/10.1007/978-3-030-37618-5_20
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