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Make Group Detection More Human

Explore group detection in various networks using sociology, biology, and computer science principles. Investigate community structures, algorithms, and challenges faced in detecting groups. Join us in testing and evaluating new approaches with real-world data.

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Make Group Detection More Human

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Presentation Transcript

  1. Make Group Detection More Human MotaharehEslamiMehdiabadi Cutlure as Data Fall 2012

  2. 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!

  3. 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

  4. 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

  5. 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)

  6. Data • Step 1:Interview • Name the clusters • Change the clustering as they want • Tell us their idea! • ……. • Step 2:Online Application • Join us soon…!

  7. CDA

  8. 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 MichelineKamber. Data mining: concepts and techniques. Morgan Kaufmann, 2006. • …

  9. Questions?

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