XiaoSen Lee created SPARK-17383:
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Summary: improvement LabelPropagation of graphx lib
Key: SPARK-17383
URL: https://issues.apache.org/jira/browse/SPARK-17383
Project: Spark
Issue Type: Improvement
Components: GraphX
Affects Versions: 2.1.0
Reporter: XiaoSen Lee
In the labelPropagation of graphx lib, node is initialized with a unique
label and at every step each node adopts the label that most of its neighbors
currently have, but ignore the label it currently have. I think it is
unreasonable, because the labe a node had is also useful. When a node trend to
has a stable label, this means there is an association between two iterations,
so a node not only affected by its neighbors, but also its current label.
so I change the code, and use both the label of its neighbors and itself.
This iterative process densely connected groups of nodes form a consensus on a
unique label to form
communities. But the communities of the LabelPropagation often discontinuous.
Because when the label that most of its neighbors currents have are many,e.g,
node "0" has 6 neigbors labed {"1","1","2","2","3","3"},it maybe randomly
select a label. in order to get a stable label of communities, and prevent the
randomness, so I chose the max lable of node.
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