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Aggregate nearest neighbor queries return the object that minimizes an aggregate distance function with respect to a set of query points. Consider, for example, several users at specific locations (query points) that want to find the restaurant (data point), which leads to the minimum sum of distances that they have to travel in order to meet. We study the processing of such queries for the case where the position and accessibility of spatial objects are constrained by spatial (e.g., road) networks. We consider alternative aggregate functions and techniques that utilize Euclidean distance bounds, spatial access methods, and/or network distance materialization structures. Our algorithms are experimentally evaluated with synthetic and real data. The results show that their relative performance depends on the problem characteristics.
Query processing, spatial databases, spatial databases and GIS, location-dependent and sensitive.
Dimitris Papadias, Man Lung Yiu, Nikos Mamoulis, "Aggregate Nearest Neighbor Queries in Road Networks", IEEE Transactions on Knowledge & Data Engineering, vol. 17, no. , pp. 820-833, June 2005, doi:10.1109/TKDE.2005.87
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