RWBP: Detects spatial outliers using a Random Walk on Bipartite Graph

a Bipartite graph and is constructed based on the spatial and/or non-spatial attributes of the spatial objects in the dataset. Secondly, RW techniques are utilized on the graphs to compute the outlierness for each point (the differences between spatial objects and their spatial neighbours). The top k objects with higher outlierness are recognized as outliers.

Version: 1.0
Depends: RANN, igraph, lsa, SnowballC
Published: 2014-06-24
Author: Sigal Shaked & Ben Nasi
Maintainer: Sigal Shaked <shaksi at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: RWBP results


Reference manual: RWBP.pdf
Package source: RWBP_1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): RWBP_1.0.tgz, r-release (x86_64): RWBP_1.0.tgz, r-oldrel: RWBP_1.0.tgz


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