LGMLJan 1, 2020

Motivic clustering schemes for directed graphs

arXiv:2001.00278v23 citations
AI Analysis

This work addresses clustering in directed graphs for network analysis, but appears incremental as it builds on existing motif concepts without clear new applications.

The authors tackled the problem of clustering directed graphs by constructing clustering methods parameterized by motifs, but the abstract does not provide specific results or numbers.

Motivated by the concept of network motifs we construct certain clustering methods (functors) which are parametrized by a given collection of motifs (or representers).

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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