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Posted to issues@spark.apache.org by "Sean Owen (JIRA)" <ji...@apache.org> on 2016/07/01 12:55:11 UTC
[jira] [Updated] (SPARK-15880) PREGEL Based Semi-Clustering
Algorithm Implementation using Spark GraphX API
[ https://issues.apache.org/jira/browse/SPARK-15880?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Sean Owen updated SPARK-15880:
------------------------------
Target Version/s: (was: 2.0.0)
> PREGEL Based Semi-Clustering Algorithm Implementation using Spark GraphX API
> ----------------------------------------------------------------------------
>
> Key: SPARK-15880
> URL: https://issues.apache.org/jira/browse/SPARK-15880
> Project: Spark
> Issue Type: New Feature
> Components: GraphX
> Reporter: R J
> Priority: Minor
> Attachments: pregel_paper.pdf
>
> Original Estimate: 672h
> Remaining Estimate: 672h
>
> The main concept of Semi-Clustering algorithm on top of social graphs are:
> - Vertices in a social graph typically represent people, and edges represent connections between them.
> - Edges may be based on explicit actions (e.g., adding a friend in a social networking site), or may be inferred from people’s behaviour (e.g., email conversations or co-publication).
> - Edges may have weights, to represent the interactions frequency or strength.
> - A semi-cluster in a social graph is a group of people who interact frequently with each other and less frequently with others.
> - What distinguishes it from ordinary clustering is that, a vertex may belong to more than one semi-cluster.
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