CREST/SSE Workshop

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Can Software Systems Engineers collaborate with Social Computing Scientists?

Can Software Systems Engineers collaborate with Social Computing Scientists?

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  • 1. Personalisation, Recommender Systems SSE - CREST Workshop October 1, 2010
  • 2. 1. introductions
  • 3. ● licia capra ● neal lathia (me) ● giovanni quattrone ● michalis christodoulou ● afra mashhadi ● lucia del prete ● valentina zanardi ● more tba
  • 4. 2. research perspective
  • 5. people i seek places things events information
  • 6. connect information systems people,places, things,events,info
  • 7. information systems extract from people,places, things,events,info
  • 8. information systems insert to people,places, things,events,info
  • 9. produce/consume information systems people,places, things,events,info
  • 10. prosume information systems people,places, things,events,info
  • 11. mobile services people,places, things,events, info information systems people,places, things,events,info
  • 12. social context
  • 13. urban context
  • 14. data-centric research preferences digital footprints social connections
  • 15. information is abundant ubiquitously accessible heterogeneous widely distributed
  • 16. an example
  • 17. an example information is abundant ubiquitously accessible heterogeneous widely distributed
  • 18. an example
  • 19. an example
  • 20. x 600,000 how do we use the system?
  • 21. x 600,000 how do we (group) use the system?
  • 22. x 600,000 how do we (people) use the system?
  • 23. x 600,000 what can we do with this data?
  • 24. x 600,000 what can we do with this data? address information abundance: ● filter, personalise, rank ● implicit behaviours to relevant, accurate, (timely) notifications
  • 25. 3. discussion/relevance
  • 26. 1. social computing techniques are starting to be used to solve software engineering tasks
  • 27. 2. can software engineering techniques be used to solve social computing tasks?
  • 28. opportunities ● we look at similar problems, in different contexts ● we use similar terms, but with different interpretations ● we adopt different solutions, that may be applicable
  • 29. opportunities ● data collection vs. requirements engineering ● context-awareness vs. task- orientation ● scalability (machine learning) vs. scalability (systems engineering)
  • 30. Personalisation, Recommender Systems SSE - CREST Workshop October 1, 2010 find me: @neal_lathia http://www.cs.ucl.ac.uk/staff/n.lathia