1. Outline Music Recommendation Approaches Examples Conclusions and future work
Recent Development at INESC Porto on Palco
Principal 3.0
Beatriz Mora
May 13, 2010

2. Outline Music Recommendation Approaches Examples Conclusions and future work
Music Recommendation Approaches
Content-based
Context-based
Hybrid
Examples
Conclusions and future work

3. Outline Music Recommendation Approaches Examples Conclusions and future work
Content-based: Music signal
• Frequency domain.
• Timbral descriptors extracted from the music audio signal.

4. Outline Music Recommendation Approaches Examples Conclusions and future work
Content-based: Distance audio matrix
• Euclidean distance.
• Matrix of distances
between all songs.
• Musical matching.
• Sorted distance song
rank.

5. Outline Music Recommendation Approaches Examples Conclusions and future work
Context-based: Latent Semantic Analysis (LSA)
is a technique used in natural language processing, in particular in
vectorial semantics, for analyzing relationships between a set of
documents and the terms they contain by producing a set of
concepts related to the documents and terms, Wikipedia.
• Word correlations.
• Reduce dimension.

6. Outline Music Recommendation Approaches Examples Conclusions and future work
Context-based: Latent Semantic Analysis (LSA)
• Word: Tag.
• Concept: Group of
tags.

7. Outline Music Recommendation Approaches Examples Conclusions and future work
Hybrid: weighted and cascade
Hybrid is a combination of the two previous approaches. There
are two methods:
• Hybrid-weighted.

8. Outline Music Recommendation Approaches Examples Conclusions and future work
Hybrid: weighted and cascade
Hybrid is a combination of the two previous approaches. There
are two methods:
• Hybrid-weighted. • Hybrid-cascade.

9. Outline Music Recommendation Approaches Examples Conclusions and future work
Jazz seed song
Content-based LSA-based
Hybrid-weighted Hybrid-cascade

10. Outline Music Recommendation Approaches Examples Conclusions and future work
Jazz seed song
Content-based LSA-based
Same timbre content Same band
Different genre Same genre
Hybrid-weighted Hybrid-cascade
New bands Same band as seed song
Same genre Same genre

11. Outline Music Recommendation Approaches Examples Conclusions and future work
Rock seed song
Content-based LSA-based
Hybrid-weighted Hybrid-cascade

12. Outline Music Recommendation Approaches Examples Conclusions and future work
Rock seed song
Content-based LSA-based
Same genre Same band
Hybrid-weighted Hybrid-cascade
New bands New bands
Same genre

13. Outline Music Recommendation Approaches Examples Conclusions and future work
Conclusions
• Audio is relevant and gives us a very wide music
recommendation.

14. Outline Music Recommendation Approaches Examples Conclusions and future work
Conclusions
• Audio is relevant and gives us a very wide music
recommendation.
• LSA limits the recommendations by “our” concepts.

15. Outline Music Recommendation Approaches Examples Conclusions and future work
Conclusions
• Audio is relevant and gives us a very wide music
recommendation.
• LSA limits the recommendations by “our” concepts.
• Which kind of music would we like to discover?.

16. Outline Music Recommendation Approaches Examples Conclusions and future work
Future work
• Optimize audio analysis.

17. Outline Music Recommendation Approaches Examples Conclusions and future work
Future work
• Optimize audio analysis.
• Look for new descriptors in the audio that can help to
distinguish genres.

18. Outline Music Recommendation Approaches Examples Conclusions and future work
Future work
• Optimize audio analysis.
• Look for new descriptors in the audio that can help to
distinguish genres.
• Collaborative filtering.