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NET-DBSCAN: clustering the nodes of a dynamic linear network

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NET-DBSCAN, a method for clustering the nodes of a linear network, whose edges may be temporarily inaccessible, is introduced. The new method extends the idea of a well-known spatial clustering method, named density-based spatial clustering of applications with noise (DBSCAN). The new algorithm is described in detail and through a series of examples. A prototype system, which implements the algorithm, developed in Java and tested through a series of synthetic networks, is also presented. Finally, the application of NET-DBSCAN method to support real-world situations is briefly discussed.
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Keywords: Clustering; Data mining; Dynamic linear networks; Graphs; Spatio-temporal analysis

Document Type: Research Article

Affiliations: Department of Geography, Harokopio University of Athens, 17671 Kallithea, Athens, Greece

Publication date: January 1, 2007

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