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• W2000480596 abstract "In this paper, we present an original network graph embedding to speed-up distance-range and k-nearest neighbor queries in (weighted) graphs. Our approach implements the paradigm of filter-refinement query processing and can be used for proximity queries on both static as well as dynamic objects. In particular, we present how our embedding can be used to compute a lower and upper bounding filter distance which approximates the true shortest path distance significantly better than traditional filters, e.g. the Euclidean distance. These distance approximations can be used within a filter step to prune true drops and true hits as well as in the refinement step in order to guide an informed A* search. Our experimental evaluation on several real-world data sets demonstrates a significant performance boosting of our proposed concepts over existing work." @default.
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• W2000480596 date "2007-01-01" @default.
• W2000480596 modified "2023-10-02" @default.
• W2000480596 title "Proximity queries in large traffic networks" @default.
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• W2000480596 doi "https://doi.org/10.1145/1341012.1341040" @default.
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