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https://issues.apache.org/jira/browse/FLINK-2310?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14662689#comment-14662689
]
ASF GitHub Bot commented on FLINK-2310:
---------------------------------------
Github user shghatge commented on the pull request:
https://github.com/apache/flink/pull/892#issuecomment-128866366
I made some of the changes mentioned. But there was a problem in replacing
the getTriplets() and flatMap. When I use this method
private static final class ReduceN implements
NeighborsFunctionWithVertexValue<Long,Tuple2<Double, HashSet<Long>> ,Double,
Tuple3<Long, Long, Double>> {
@Override
public void iterateNeighbors(
Vertex<Long, Tuple2<Double, HashSet<Long>>>
vertex,
Iterable<Tuple2<Edge<Long, Double>,
Vertex<Long, Tuple2<Double, HashSet<Long>>>>> neighbors,
Collector<Tuple3<Long, Long, Double>> out)
throws Exception {
for(Tuple2<Edge<Long, Double>, Vertex<Long,
Tuple2<Double, HashSet<Long>>>> neighbor : neighbors) {
HashSet<Long> intersection =
vertex.getValue().f1;
intersection.retainAll(neighbor.f1.getValue().f1);
for(long l : intersection) {
System.out.println(neighbor.f1.getId()+" "+l);
out.collect(new Tuple3<Long,
Long, Double>(neighbor.f1.getId(), l, vertex.getValue().f0));
}
}
}
}
For some reason the
> Add an Adamic-Adar Similarity example
> -------------------------------------
>
> Key: FLINK-2310
> URL: https://issues.apache.org/jira/browse/FLINK-2310
> Project: Flink
> Issue Type: Task
> Components: Gelly
> Reporter: Andra Lungu
> Assignee: Shivani Ghatge
> Priority: Minor
>
> Just as Jaccard, the Adamic-Adar 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 Adamic-Adar 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 out-edges
> 3). Weigh the edges with the Adamic-Adar 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/fast-algorithm-to-compute-adamic-adar
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