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Clustering Objects on a Spatial Network

Summary: Clustering objects on edges of a spatial network using shortest-path distance, not Euclidean. Introduces partitioning, density-based, and hierarchical variants; evaluated on road networks; scalable, effective at identifying network-aware clusters. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
3539
Venue
SIGMOD
Year
2004
Pagerank
4.6967024e-05
Overall Rank
7,608 | 47.08%
DOI
-

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 4 of 4 citing papers.

Rank Citing Paper Year Venue Pagerank
2,085 Capacity Constrained Assignment in Spatial Databases 2008 SIGMOD 9.5804907e-05
6,093 Density-based Place Clustering in Geo-Social Networks 2014 SIGMOD 5.2131159e-05
9,495 Fast Network K-function-based Spatial Analysis 2022 VLDB 4.3341665e-05
11,499 Fast Augmentation Algorithms for Network Kernel Density Visualization 2021 VLDB 4.1945683e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 6 of 6 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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