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Community detection in semantic graph

Community detection in semantic graph. who am I?. I defined my self as. attribute. ?. attribute. attribute. I can be define with my main attribute. attribute. attribute. attribute. but more precisely with a melting pot of my attributes. attribute. attribute. attribute.

kibo-morrison
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Community detection in semantic graph

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  1. Community detection in semantic graph

  2. who am I?

  3. I defined my self as attribute ? attribute attribute

  4. I can be define with my main attribute attribute attribute attribute

  5. but more precisely with a melting pot of my attributes attribute attribute attribute

  6. but I'm also defined by my social network ?

  7. I can be defined by my main collaborators

  8. but also by a melting pot of these collaborators

  9. who are we?

  10. instance of connected individuality

  11. the majority generally define the group

  12. but every collaboration build the identity of a community

  13. different levels of cohesion

  14. algorithme LP/RAK don't we have better descriptors than random labels ?

  15. I tag, so I am!

  16. we tag and collaborate, who are we? we are 'semantic web', 'web2.0', 'strategic watch'

  17. propagation de tags "interaction creates similarity, while similarity creates interaction" [mika 2005] éoliennes éoliennes

  18. but we still have tag propagation

  19. to infer this we need some knowledge

  20. = 3 2 + 1

  21. = 3 2 + 1

  22. = 6 3 + 2 + 1

  23. algorithm LP/RAK sport condiment rugby, foot hockey salt, water sport pepper, wine condiment sport condiment foot, cine mustard semantic propagation of tags

  24. Applied to ademe's Ph.D. network biomass energy efficiency air pollution climat change soil pollution

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