This document discusses combining social music data and the semantic web for music recommendation systems. It outlines how social music data from services like Last.fm can be modeled and interconnected using ontologies like FOAF, SIOC and MOAT. This unified semantic social music data can then be used for music recommendations by exploring relationships between artists, genres, social connections and tagged content. Examples of recommendation approaches are provided that leverage different aspects of the semantic social music graph.

1. Combining Social Music and Semantic Web
for music-related recommender systems
Alexandre Passant, DERI, NUI Galway
Yves Raimond, BBC, UK
Social Data on The Web @ ISWC2008
Karlsruhe, 27th October 2008
http://flickr.com/photos/8049973@N03/2656140464/ by wolf.tone

2. Agenda
• Web 2.0, Social Music and the
Semantic Web
• Identity, social-networking and social
data with FOAF and SIOC
• Linking Open Data and augmented
tagging with MOAT
• Recommendation systems
• Examples of LOD-based
recommendations
• Use-cases

3. Web 2.0 and Social Music
• Term coined from last.fm
• In this talk:
• Social networks from music-related services
• Interlinking music-related data
• Music-related weblogging and tagging

4. Semantic Social Music
Web:
Hyperlink Documents and
hyperlinks

5. Semantic Social Music
Alexandre Passant Listens to Franz Ferdinand Interpretation
Web:
Hyperlink Documents and
hyperlinks

6. Semantic Social Music
foaf:Person mo:MusicArtist
Semantic Web:
rdf:type rdf:type Data, models
and relationships
<http://zitgist.com/music/artist/aa7a2827-
<http://dbtune.org/last-fm/terraces> ex:listensTo
f74b-473c-bd79-03d065835cf7>
Alexandre Passant Listens to Franz Ferdinand Interpretation
Web:
Hyperlink Documents and
hyperlinks

7. Limits of Web 2.0 services
• Data models
• Each service uses its own model / API
• Need to build specific services
• Documents, hyperlinks rather than concepts
and relationships
• Closed worlds
• How to share data and connect people
between websites ?
• Social Network Fatigue (Fitzpatrick, 2007)
• The Semantic Web can help !

8. Unifying Social Networks

9. Unifying Social Networks

10. FOAF exporters examples

11. Unifiying identity
• One exporter = One URI
• lastfm:bob, myspace:bobby,
facebook:bob77 ...
• A need to unify one’s identity across
services by defining equivalent URIs
• Explicit: owl:sameAs
• Implicit: foaf:email, foaf:openid
• Both use reasoning principles
• Interlinking distributed social networks

12. Merging networks
• A complete decentralized social graph
• Open, distributed, build on standards
• From various services
(Kinsella, 2007)

13. Modeling Web 2.0 content
• SIOC: Semantically-Interlinked Online
Communities
• http://sioc-project.org
• An ontology to describe activities of
online communities and their Social
Media Contributions (SMC)
• Common semantics for SMC modeling
• Reusing existing ontologies (FOAF, DC ...)
• W3C Member submission, June 2007
• http://www.w3.org/Submission/2007/02

14. The SIOC Model
http://rdfs.org/sioc/spec

15. People, accounts and data
http://www.johnbreslin.com/blog/2008/01/04/dataportabilityorg-web-standards-sioc-and-foaf/

16. The LOD Initiative
• Linking Open Data
• http://linkeddata.org
• Lots of information available on the Web
• Closed world, proprietary data silos
• Provide it in RDF and interlink it !
• From documents to machine-understandable data
• Use links to discover data by browsing the GGG
• Open licensing policy
• ISWC2008 tutorial on Linked Data

17. The LOD cloud
http://richard.cyganiak.de/2007/10/lod/

18. Music-related open data
• http://dbtune.org
• Music-related RDF platform
• LOD-exporters for major music
databases and social services
• MusicBrainz, Jamendo
• Last.fm, MySpace
• Interlinked with references datasets
• Geonames, DBPedia, riese, FOAF
• Advanced querying and browsing features

19. Tagging with URIs ?
• Indexing data with Semantic Web
concepts defined by URIs
• Solves ambiguity / heterogeneity problems
thanks to understandable identifiers
• Interlinking content thanks to Linked Data
• Challenges
• How to find URIs related to a given tag
and define new ones ?
• How to let people easily bridge this gap
between tagging and semantic indexing ?

20. MOAT
• Meaning Of A Tag
• http://moat-project.org
• A model to represent the meaning of tags
• “apple” can refer to various things, but when
I tag this blog post with it, I mean the record
company, not the fruit
• A collaborative and open-source
framework
• A tag server to define and share meanings
• http://lodr.info

21. Music recommendations
• Collaborative filtering
• http://last.fm/
• Long tail?
• Content-based analysis
• Texture, rhythm, harmony, ...
• http://www.mufin.com/
• Long tail!
• Lack of cultural context
• Hybrid recommenders

22. Linked Data !
• Lots of cultural context
• Suggests musical resources using
linked data:
• Distributed social networks
• SMC and tagged content
• Linked data available within the LOD
project
• Related work: FOAF-ing the music

23. Examples

24. Social Networking
• You may like what your friends are
listening to ...
:alex foaf:knows :yves
foaf:topic_interest
dbpedia:Ramones

25. Social Networking
• ... and also the friends of your friends ...
:alex foaf:knows :yves foaf:knows :tom
foaf:topic_interest foaf:topic_interest
dbpedia:Ramones dbpedia:Rancid

26. Social Networking
• ... from any service
:alex foaf:knows :yves foaf:knows :tom
foaf:topic_interest foaf:topic_interest
dbpedia:Ramones dbpedia:Rancid

27. Using LOD
• You like a band, what about using
DBpedia to see if you may like ...
:alex foaf:topic_interest dbpedia:Beastie_Boys

28. Using LOD
• Bands that share concerts with them ?
dbpedia:Bad_Brains
p:associatedActs
:alex foaf:topic_interest dbpedia:Beastie_Boys

29. Using LOD
• Their solo members ?
dbpedia:Bad_Brains
p:associatedActs
:alex foaf:topic_interest dbpedia:Beastie_Boys
p:currentMembers
dbpedia:Adam_Yauch

30. Using LOD
• Bands from the same music genre ?
dbpedia:Bad_Brains dbpedia:Hardcore_Punk
p:associatedActs p:genre p:genre
:alex foaf:topic_interest dbpedia:Beastie_Boys dbpedia:Black_Flag_(band)
p:currentMembers
dbpedia:Adam_Yauch

31. Using LOD
• Or even ... somehow related artists ?
dbpedia:Bad_Brains dbpedia:Hardcore_Punk
p:associatedActs p:genre p:genre
:alex foaf:topic_interest dbpedia:Beastie_Boys dbpedia:Black_Flag_(band)
p:currentMembers
dbpedia:Adam_Yauch dbpedia:B._B._King
skos:subject skos:subject
dbpedia:Category:American_vegatarians

32. SMC and tagged content
• Tag blog posts using SIOC and MOAT ...
dbpedia:The_Clash
sioc:topic
:blogPost1
rdf:type
sioct:BlogPost
sioc:creator_of
:alex

33. SMC and tagged content
• ... while people tag pictures ...
dbpedia:The_Clash dbpedia:Joe_Strummer
sioc:topic sioc:topic
:blogPost1 exif:IFD rdf:type :picture1
rdf:type
sioct:BlogPost
sioc:creator_of sioc:creator_of
:alex :bob

34. SMC and tagged content
• ... find related content ...
p:pastMembers
dbpedia:The_Clash dbpedia:Joe_Strummer
sioc:topic sioc:topic
:blogPost1 exif:IFD rdf:type :picture1
rdf:type
sioct:BlogPost
sioc:creator_of sioc:creator_of
:alex :bob

35. SMC and tagged content
• ... once again, everything is distributed
p:pastMembers
dbpedia:The_Clash dbpedia:Joe_Strummer
sioc:topic sioc:topic
:blogPost1 exif:IFD rdf:type :picture1
rdf:type
sioct:BlogPost
sioc:creator_of sioc:creator_of
:alex :bob

36. Use cases

37. Simple recommendation
• Artists that a friend of mine is
interested in
• SELECT ?artist
WHERE {
<$uri> foaf:knows [
foaf:topic_interest ?artist .
] }

38. Content-based
• SELECT ?track1 ?track2
WHERE {
<$uri> foaf:topic_interest ?artist .
?artist foaf:made ?track1 .
?track1 mo:similar_to ?track2 .
}
• http://dbtune.org/henry

39. Mixing both

SELECT ?artist2
WHERE {
<$uri> foaf:knows
[ foaf:topic_interest ?artist ] .
?artist a mo:MusicArtist; foaf:made ?
track1.
?track1 mo:similar_to ?track2.
?artist2 foaf:made ?track2.
}

40. Event + geolocation

41. Content-based

43. Personal music collection

44. A record I don't yet own

45. Facet browsing for artist
• http://apassant.net/home/2008/10/
musicrec
• DBpedia based
• Filtering of relevant properties

46. Future work
• Origin:
• A web resource (the user)‫‏‬
• Target:
• A web resource (the recommendation)‫‏‬
• Problem:
• Finding a path between the origin and the
target that goes nearby other “constraints”
web resources
• Interests, personal music collection,
listening habits, friends, etc.

47. Thank you ! Any questions ?
http://flickr.com/photos/8049973@N03/2656140464/ by wolf.tone