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کامپیوتر و شبکه::
زیرفضا
Whereas the individual outlier is highly similar to other nodes in the subgraph, it deviates sig- nificantly with respect to a subset of significant attributes called subspaces.
GoutRank addresses two problems: (1) the problem of selecting subgraphs with their individual subspaces and (2) the problem of scoring of nodes in these multiple subspaces.
It uses graph clustering techniques and subspace analysis as preproces- sing steps for generating the outlier rankings.
Clustering on multi- layer graphs via subspace analysis on grassmann manifolds.
Ranking outlier nodes in subspaces of attributed graphs.
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