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- W3005678367 abstract "Network motifs are recurring patterns of interconnections that are significantly over represented. The study of network motifs can provide significant new insights into the functionality of these motifs in the network. Previously developed algorithms for discovering network motifs have been limited to motifs of 6 to 8 nodes. New methods are necessary to identify larger network substructures and functional motifs. The aim here is to apply Map-Reduce concept for mining large motifs from networks. The performance evaluation shows our algorithm can detect larger motifs in large size networks and has good scalability." @default.
- W3005678367 created "2020-02-24" @default.
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- W3005678367 date "2019-07-01" @default.
- W3005678367 modified "2023-09-26" @default.
- W3005678367 title "Map Reduce Framework for Network Motif Finding" @default.
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- W3005678367 doi "https://doi.org/10.1109/icicict46008.2019.8993245" @default.
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