2008 IEEE 24th International Conference on Data Engineering (2008)
Apr. 7, 2008 to Apr. 12, 2008
Man Lung Yiu , Department of Computer Science, Aalborg University, DK-9220 Aalborg, Denmark. firstname.lastname@example.org
Nikos Mamoulis , Department of Computer Science, University of Hong Kong, Pokfulam Road, Hong Kong. email@example.com
Panagiotis Karras , Department of Informatics, University of Zurich, CH-8050 Zurich, Switzerland. firstname.lastname@example.org
We identify and formalize a novel join operator for two spatial pointsets P and Q. The common influence join (CIJ) returns the pairs of points (p, q), pP, qQ, such that there exists a location in space, being closer to p than to any other point in P and at the same time closer to q than to any other point in Q. In contrast to existing join operators between pointsets (i.e., -distance joins and k-closest pairs), CIJ is parameter-free, providing a natural join result that finds application in marketing and decision support. We propose algorithms for the efficient evaluation of CIJ, for pointsets indexed by hierarchical multi-dimensional indexes. We validate the effectiveness and the efficiency of these methods via experimentation with synthetic and real spatial datasets. The experimental results show that a non-blocking algorithm, which computes intersecting pairs of Voronoi cells on-demand, is very efficient in practice, incurring only slightly higher I/O cost than the theoretical lower bound cost for the problem.
P. Karras, M. L. Yiu and N. Mamoulis, "Common Influence Join: A Natural Join Operation for Spatial Pointsets," 2008 IEEE 24th International Conference on Data Engineering(ICDE), Cancun, Mexico, 2008, pp. 100-109.