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COMMIT: A Scalable Approach to Mining Communication Motifs from Dynamic Networks

Summary: COMMIT scales mining of communication motifs in dynamic networks by turning evolving graphs into a sequence database and pruning the search. Up to 100x speedups vs baselines; motifs reveal recurring interaction patterns and social-network influence. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5005
Venue
SIGMOD
Year
2015
Pagerank
6.5605514e-05
Overall Rank
3,987 | 72.27%
DOI
10.1145/2733272.2737791

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

Rank Cited Paper Year Venue Pagerank
951 Comparing Stars: On Approximating Graph Edit Distance 2009 VLDB 0.00015106325
1,089 GRAMI: Frequent Subgraph and Pattern Mining in a Single Large Graph 2014 VLDB 0.00014157922
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