MAKE GROUP DETECTION MORE HUMAN

Motahareh EslamiMehdiabadi

Cutlure as Data

Fall 2012

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GROUPS

Communities, clusters or modules Community structure: many relations within

a group/ few relations between groups Independent Compartments

Detecting groups (communities) Sociology Biology Computer Science

Hard problem Not yet satisfactorily solved!

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WHY DETECTING GROUPS?

Many real networks have community structures. Families Friendship circles Villages and Towns Virtual groups on internet …

Clustering web clients who are geographically near to each other

Identifying clusters of customers with similar interests

Ad-hoc networks Classification of vertices

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THE CHALLENGE

Several group detection algorithms No one cannot state which method (or subset

of methods) is the most reliable one in applications.

Testing and Evaluation Using simple benchmark graphs

Debating over complexity and time Limited evaluation measures

A LFR benchmark graph

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A NEW APPROACH OF EVALUATION

Asking people to evaluate! Facebook Network

Use efficient and popular algorithms Grivan-Newman (GN) Markov Clustering (MCL) Clauset-Newman –More (CNM)

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DATA

Step 1:Interview Name the clusters Change the clustering as they want Tell us their idea! …….

Step 2:Online Application

Join us soon…!

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CDA

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REFERENCES Fortunato, Santo. Community detection in graphs. Physics

Reports 486.3 (2010): 75-174. Lancichinetti, Andrea, Santo Fortunato, and Filippo Radicchi.

Benchmark graphs for testing community detection algorithms. Physical Review E 78.4 (2008): 046110.

Han, Jiawei, and Micheline Kamber. Data mining: concepts and techniques. Morgan Kaufmann, 2006.

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QUESTIONS?