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ASF GitHub Bot commented on FLINK2310:

Github user andralungu commented on the pull request:
https://github.com/apache/flink/pull/892#issuecomment128923829
Hi @shghatge,
Remember the git rebase command we talked about when you were in Berlin? You should revert
the last commit and rebase instead... right now it looks like 15 other people contributed
to your code ;) This is because you merged the master into your branch.
> Add an AdamicAdar Similarity example
> 
>
> Key: FLINK2310
> URL: https://issues.apache.org/jira/browse/FLINK2310
> Project: Flink
> Issue Type: Task
> Components: Gelly
> Reporter: Andra Lungu
> Assignee: Shivani Ghatge
> Priority: Minor
>
> Just as Jaccard, the AdamicAdar algorithm measures the similarity between a set of nodes.
However, instead of counting the common neighbors and dividing them by the total number of
neighbors, the similarity is weighted according to the vertex degrees. In particular, it's
equal to log(1/numberOfEdges).
> The AdamicAdar algorithm can be broken into three steps:
> 1). For each vertex, compute the log of its inverse degrees (with the formula above)
and set it as the vertex value.
> 2). Each vertex will then send this new computed value along with a list of neighbors
to the targets of its outedges
> 3). Weigh the edges with the AdamicAdar index: Sum over n from CN of log(1/k_n)(CN is
the set of all common neighbors of two vertices x, y. k_n is the degree of node n). See [2]
> Prerequisites:
>  Full understanding of the Jaccard Similarity Measure algorithm
>  Reading the associated literature:
> [1] http://social.cs.uiuc.edu/class/cs591kgk/friendsadamic.pdf
> [2] http://stackoverflow.com/questions/22565620/fastalgorithmtocomputeadamicadar

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