Proximity queries in large traffic networks

Hans-Peter Kriegel, Peer Kröger, Peter Kunath, Matthias Renz, Tim Schmidt
2007 Proceedings of the 15th annual ACM international symposium on Advances in geographic information systems - GIS '07  
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
more » ... ters, 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.
doi:10.1145/1341012.1341040 dblp:conf/gis/KriegelKKRS07 fatcat:yxn6vq5yzrg73kixpw2ffxurr4