Distributed Graph Analytics (DGA) is a compendium of graph analytics written for Bulk-Synchronous-Parallel (BSP) processing frameworks such as Giraph and GraphX. The analytics included are High Betweenness Set Extraction, Weakly Connected Components, Page Rank, Leaf Compression, and Louvain Modularity.
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louvain modularity in Graphx seems to have a problem #94
When compute deltaQ in q method ,deltaQ = k_i_in - (k_i * sigma_tot / M) seems not right. Here M is degree of Graph(2 edge, here may be total edge weight2). According the paper,we can use relative value of Q to choose neighbor ( that is k_i_in - sigma_tot*k_i/m ). so here M should be replaced by M/2(just m in paper) . is right or am I wrong?
When compute deltaQ in
q
method ,deltaQ = k_i_in - (k_i * sigma_tot / M)
seems not right. Here M is degree of Graph(2 edge, here may be total edge weight2). According the paper,we can use relative value of Q to choose neighbor ( that isk_i_in - sigma_tot*k_i/m
). so here M should be replaced by M/2(just m in paper) . is right or am I wrong?https://github.com/Sotera/distributed-graph-analytics/blob/c22aaf4ba56a50276607939f8fad4df5469f29ca/dga-graphx/src/main/scala/com/soteradefense/dga/graphx/louvain/LouvainCore.scala#L263