1. Multi domain recommendation system
MOVIES BOOKS MUSIC

2. Multi domain recommendation system
MOVIES BOOKS MUSIC

3. Multi domain recommendation system
MOVIES BOOKS MUSIC

4. Multi domain recommendation system
MOVIES BOOKS MUSIC

5. Multi domain recommendation system
MOVIES BOOKS MUSIC

6. Multi domain recommendation system
MOVIES BOOKS MUSIC

7. Multi domain recommendation system
MOVIES BOOKS MUSIC

8. Multi domain recommendation system
MOVIES BOOKS MUSIC

9. Multi domain recommendation system
MOVIES BOOKS MUSIC

10. User characterization by item preferences
Movies Books
John likes:
Mary likes:
Recommendations:
Tom likes:
??

11. User characterization by item preferences
Movies Books
John likes:
Mary likes:
Recommendations (domain-specific):
Popular books suggested
Tom likes: since no prior information
is available

12. User characterization by item preferences
Movies Books
John likes:
Mary likes:
Recommendations (multi-domain):
Based on Tom’s movie
preferences, and other
Tom likes: users’ cross-domain
information

13. User characterization by item preferences
Movies Books
John likes:
Mary likes:
Tom likes:

14. User characterization by item preferences
Movies Books
John likes:
Mary likes:
Recommendations (multi-domain):
Tom likes:

15. User characterization by item preferences
Movies Books
John likes:
Mary likes:
Recommendations (multi-domain):
Tom likes:

16. New items or sparsely rated items
• New movie
• Very few user ratings
• Cannot be correctly
classified and recommended
• Use meta information
• Easier to identify similar
items

17. New items or sparsely rated items
Tom likes:

18. New items or sparsely rated items
Tom likes: Recommendations:
OOPS!

19. New items or sparsely rated items
Tom likes: Recommendations:
OK!

20. # items rated by user Average squared error
User
Domain Specific Recommendation
# items rated by user Average squared error
User
Multi Domain Recommendation

21. Domain Specific Recommendation Multi Domain Recommendation
Average squared error
Average squared error
62.56% decrease
User
in root mean User
squared error
# items rated by user
# items rated by user

22. Quantitative Improvement
Method Percentage Books Music Video
accuracy (220,000 (80,000 (22,000
ratings) ratings) ratings)
Collaborative 49.4 50.21 48.1 47.7
Filtering
(domain
specific)
Collaborative 63.2 65.67 60.22 57.34
Filtering
(multi-domain)
Hybrid 76.4 77.13 75.11 73.87
(Multi-domain
Collaborative +
content based)

23. Aastha Jain