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From vasia <...@git.apache.org>
Subject [GitHub] flink pull request: [FLINK-3780] [gelly] Jaccard Similarity
Date Thu, 19 May 2016 14:56:00 GMT
Github user vasia commented on a diff in the pull request:

    --- Diff: docs/apis/batch/libs/gelly.md ---
    @@ -2051,6 +2052,26 @@ The algorithm takes a directed, vertex (and possibly edge) attributed
graph as i
     vertex represents a group of vertices and each edge represents a group of edges from
the input graph. Furthermore, each
     vertex and edge in the output graph stores the common group value and the number of represented
    +### Jaccard Index
    +#### Overview
    +The Jaccard Index measures the similarity between vertex neighborhoods. Scores range
from 0.0 (no common neighbors) to
    +1.0 (all neighbors are common).
    +#### Details
    +Counting common neighbors for pairs of vertices is equivalent to counting the two-paths
consisting of two edges
    +connecting the two vertices to the common neighbor. The number of distinct neighbors
for pairs of vertices is computed
    +by storing the sum of degrees of the vertex pair and subtracting the count of common
neighbors, which are double-counted
    +in the sum of degrees.
    +The algorithm first annotates each edge with the endpoint degree. Grouping on the midpoint
vertex, each pair of
    +neighbors is emitted with the endpoint degree sum. Grouping on two-paths, the common
neighbors are counted.
    +#### Usage
    +The algorithm takes a simple, undirected graph as input and outputs a `DataSet` of tuples
containing two vertex IDs,
    +the number of common neighbors, and the number of distinct neighbors. The graph ID type
must be `Comparable` and
    --- End diff --
    Ah great! Can you add this here?

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