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From "Lee Dongjin (JIRA)" <>
Subject [jira] [Commented] (SPARK-15880) PREGEL Based Semi-Clustering Algorithm Implementation using Spark GraphX API
Date Mon, 09 Jan 2017 13:46:58 GMT


Lee Dongjin commented on SPARK-15880:

[~sowen] Thanks for your comment. However, I expect that the output will be similar to ConnectedComponents
or StronglyConnectedComponents algorithm in GraphX, which are not RDD-Based. Given that, isn't
it worth to add?

> PREGEL Based Semi-Clustering Algorithm Implementation using Spark GraphX API
> ----------------------------------------------------------------------------
>                 Key: SPARK-15880
>                 URL:
>             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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