This document summarizes a workshop on personalization and recommender systems. It introduces the presenters and discusses using information systems to extract, connect, and insert information from people, places, things, and events to produce and consume information. It also discusses opportunities to apply techniques from social computing to software engineering problems and vice versa, such as using data collection methods for requirements engineering and applying context awareness and machine learning to systems engineering challenges.

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

6. people
i seek places
things
events
information

7. connect information
systems
people,places,
things,events,info

8. information
systems
extract from people,places,
things,events,info

9. information
systems
insert to people,places,
things,events,info

10. produce/consume
information
systems
people,places,
things,events,info

11. prosume
information
systems
people,places,
things,events,info

12. mobile services
people,places,
things,events, info
information
systems
people,places,
things,events,info

13. social context

14. urban context

15. data-centric research
preferences
digital footprints
social connections

16. information is
abundant
ubiquitously accessible
heterogeneous
widely distributed

17. an example

18. an example
information is
abundant
ubiquitously accessible
heterogeneous
widely distributed

19. an example

20. an example

21. x 600,000
how do we use the system?

22. x 600,000
how do we (group) use the system?

23. x 600,000
how do we (people) use the system?

24. x 600,000
what can we do with this data?

25. x 600,000
what can we do with this data?
address information abundance:
● filter, personalise, rank
● implicit behaviours to relevant,
accurate, (timely) notifications

26. 3. discussion/relevance

27. 1. social computing techniques
are starting to be used to solve
software engineering tasks

28. 2. can software engineering
techniques be used to solve
social computing tasks?

29. 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

30. opportunities
● data collection vs. requirements
engineering
● context-awareness vs. task-
orientation
● scalability (machine learning)
vs. scalability (systems
engineering)

31. Personalisation, Recommender Systems
SSE - CREST Workshop October 1, 2010
find me: @neal_lathia
http://www.cs.ucl.ac.uk/staff/n.lathia