Detecting hotspots in geographic networks

K. Buchin, S. Cabello, J. Gudmundsson, M. Löffler, J. Luo, G. Rote, R.I. Silveira, B. Speckmann, T. Wolle

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

9 Citations (Scopus)
1 Downloads (Pure)

Abstract

We study a point pattern detection problem on networks, motivated by geographical analysis tasks, such as crime hotspot detection. Given a network N (for example, a street, train, or highway network) together with a set of sites which are located on the network (for example, accident locations or crime scenes), we want to find a connected subnetwork F of N of small total length that contains many sites. That is, we are searching for a subnetwork F that spans a cluster of sites which are close with respect to the network distance. We consider different variants of this problem where N is either a general graph or restricted to a tree, and the subnetwork F that we are looking for is either a simple path, a path with self-intersections at vertices, or a tree. Many of these variants are NP-hard, that is, polynomial-time solutions are very unlikely to exist. Hence we focus on exact algorithms for special cases and efficient algorithms for the general case under realistic input assumptions.
Original languageEnglish
Title of host publicationAdvances in GIScience (Proceedings of the 12th AGILE Conference, Hannover, Germany, June 2-5, 2009)
EditorsM. Sester, L. Bernard, V. Paelke
Place of PublicationBerlin
PublisherSpringer
Pages217-231
ISBN (Print)978-3-642-00317-2
DOIs
Publication statusPublished - 2009

Publication series

NameLecture Notes in Geoinformation and Cartography
ISSN (Print)1863-2246

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