Partitioning a graph by iteratively excluding edges

作者: Boriana Lubomirova Milenova , Marcos M Campos

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摘要: Methods, machines, and stored instructions are provided for partitioning a graph of nodes into clusters by iteratively excluding edges in the graph. For each node at least subset graph, module determines whether to exclude and, if so, selects exclusion edge(s) node's neighbor(s). The neighbor(s) based part on degree overlap between any subset(s) that yet not sufficiently partitioned clusters, repeats step determining selecting exclusion, or partitioned. Subset(s) already may be skipped during repeated steps.

参考文章(21)
Natalia Flora de Lima, Teresa Bernarda Ludermir, Frankenstein PSO applied to neural network weights and architectures 2011 IEEE Congress of Evolutionary Computation (CEC). pp. 2452- 2456 ,(2011) , 10.1109/CEC.2011.5949921
Ankur Narang, Jyothish Soman, Distributed Scalable Clustering and Community Detection ,(2012)
Emden R. Gansner, Yifan Hu, Methods, Systems, and Products for Graphing Data ,(2008)
Bulent Yener, Cigdem Gunduz, S. Gultekin, Method and apparatus for tissue modeling ,(2005)
Zoltan I. Gyongyi, Social affinity on the web ,(2010)