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2007
ACM

Proximity queries in large traffic networks

11 years 24 days ago
Proximity queries in large traffic networks
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. Categories and Subject Descriptors H.3.3 [INFORMATION STORAGE AND RETRIEVAL]: Information Search and Retrieval General Terms Performance Ke...
Hans-Peter Kriegel, Matthias Renz, Peer Kröge
Added 09 Nov 2009
Updated 09 Nov 2009
Type Conference
Year 2007
Where GIS
Authors Hans-Peter Kriegel, Matthias Renz, Peer Kröger, Peter Kunath, Tim Schmidt
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