[SPARK-15880] PREGEL Based Semi-Clustering Algorithm Implementation using Spark GraphX API

• Type: New Feature
• Status: Closed
• Priority: Minor
• Resolution: Won't Fix
• Component/s: GraphX
• Assignee: Unassigned
• Reporter: R J
• Created: 10/Jun/16 19:41
• Updated: 24/Jan/17 06:39
• Resolved: 24/Jan/17 06:39

Description

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.