Definition
Spatial network databases (SNDB) are becoming increasingly important since, in practice, objects can usually move only on a pre-defined set of trajectories as specified by the underlying network (road, railway, river etc.). In this case, the important measure is the network distance, i.e., the length of the shortest trajectory connecting two objects, rather than their Euclidean distance. Every spatial query type (e.g., nearest neighbors, range search, spatial joins, etc.) has a counterpart in SNDB. Consider, for instance, the road network of Fig. 1, where the rectangles correspond to hotels. If a user at location q poses the query “find the nearest hotel”, the result is b (the numbers in the figure correspond to network distance). Note that the Euclidean nearest neighbor is d, which is actually the farthest hotel in the network.
Road...
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References
Beckmann N, Kriegel HP, Schneider R, Seeger B (1990) The R*-tree: an efficient and robust access method for points and rectangles. In: SIGMOD
Cho HJ, Chung CW (2005) An efficient and scalable approach to CNN queries in a road network. In: VLDB
Dijkstra EW (1959) A note on two problems in connection with graphs. Numeriche Mathematik 1:269–271
Hjaltason G, Samet H (1999) Distance browsing in spatial databases. TODS 24(2):265–318
Hu H, Lee DL, Xu J (2006) Fast nearest neighbor search on road networks. In: EDBT
Huang X, Jensen CS, Saltenis S (2005) The islands approach to nearest neighbor querying in spatial networks. In: SSTD
Jing N, Huang YW, Rundensteiner EA (1998) Hierarchical encoded path views for path query processing: an optimal model and its performance evaluation. TKDE 10(3):409–432
Kolahdouzan M, Shahabi C (2004) Voronoi-based K nearest neighbor search for spatial network databases. In: VLDB
Kolahdouzan M, Shahabi C (2004) Continuous K-nearest neighbor queries in spatial network databases. In: STDBM
Mouratidis K, Yiu ML, Papadias D, Mamoulis N (2006) Continuous nearest neighbor monitoring in road networks. In: VLDB
Papadias D, Zhang J, Mamoulis N, Tao Y (2003) Query processing in spatial network databases. In: VLDB
Shekhar S, Liu D (1997) CCAM: a connectivity-clustered access method for networks and network computations. TKDE 19(1):102–119
Shekhar S, Yoo JS (2003) Processing in-route nearest neighbor queries: a comparison of alternative approaches. In: ACM GIS
Yiu ML, Mamoulis N, Papadias D (2005) Aggregate nearest neighbor queries in road networks. TKDE 17(6):820–833
Yiu ML, Papadias D, Mamoulis N, Tao Y (2006) Reverse nearest neighbors in large graphs. TKDE 18(4): 540–553
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Papadias, D., Yiu, M.L., Mamoulis, N., Tao, Y. (2017). Nearest Neighbor Queries in Network Databases. In: Shekhar, S., Xiong, H., Zhou, X. (eds) Encyclopedia of GIS. Springer, Cham. https://doi.org/10.1007/978-3-319-17885-1_864
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DOI: https://doi.org/10.1007/978-3-319-17885-1_864
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