Your SlideShare is downloading. ×
0
BSkyB - UCL Collaboration Workshop
BSkyB - UCL Collaboration Workshop
BSkyB - UCL Collaboration Workshop
BSkyB - UCL Collaboration Workshop
BSkyB - UCL Collaboration Workshop
BSkyB - UCL Collaboration Workshop
BSkyB - UCL Collaboration Workshop
BSkyB - UCL Collaboration Workshop
BSkyB - UCL Collaboration Workshop
BSkyB - UCL Collaboration Workshop
BSkyB - UCL Collaboration Workshop
BSkyB - UCL Collaboration Workshop
BSkyB - UCL Collaboration Workshop
BSkyB - UCL Collaboration Workshop
BSkyB - UCL Collaboration Workshop
BSkyB - UCL Collaboration Workshop
BSkyB - UCL Collaboration Workshop
BSkyB - UCL Collaboration Workshop
BSkyB - UCL Collaboration Workshop
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×
Saving this for later? Get the SlideShare app to save on your phone or tablet. Read anywhere, anytime – even offline.
Text the download link to your phone
Standard text messaging rates apply

BSkyB - UCL Collaboration Workshop

2,068

Published on

Published in: Education, Business
1 Comment
2 Likes
Statistics
Notes
No Downloads
Views
Total Views
2,068
On Slideshare
0
From Embeds
0
Number of Embeds
1
Actions
Shares
0
Downloads
1
Comments
1
Likes
2
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
No notes for slide

Transcript

  • 1. Next Generation Recommender Systems Neal Lathia & Licia Capra
  • 2. Recommender Systems: why?
  • 3. information overload
  • 4. the age of discovery
  • 5. Recommender Systems: born on the web
  • 6. source: O. Celma & P. Lamere “Music Recommendation Tutorial” ISMIR 2007
  • 7. http://www.netflixprize.com
  • 8. Users who have been like-minded in the past will be like- minded in the future.
  • 9. Recommender Systems: leaving the web behind
  • 10. recommending television
  • 11. sharing & discovering content on the move
  • 12. Recommender Systems: emerging from the web
  • 13. Recommender Systems: (some) research directions
  • 14. context time, location, social networks, groups, niche tastes, mobility
  • 15. Richer modelling of users, and the data they provide us about their tastes: accounting for social connectivity, location, time, what is being recommended: context-aware recommendations.
  • 16. Next Generation Recommender Systems Neal Lathia & Licia Capra

×