The document discusses approaches for semantically enriching folksonomies by structuring user-generated tags. It proposes a life-cycle approach involving initial automatic processing of tags to identify relationships, followed by user-centric structuring, conflict detection, and global structuring by a referent user. The goal is to turn flat folksonomies into structured folksonomies integrated with Semantic Web models while capturing diverse user perspectives.

1. From
folksonomies to
ontologies :
a socio-technical
solution
1P H I L O W E B – O c t o b e r 1 6 t h 2 0 1 0
Freddy Limpens
Edelweiss, INRIA Sophia Antipolis
Supervisors:
Fabien Gandon, Edelweiss, INRIA Sophia Antipolis
Michel Buffa, I3S, Université Nice – Sophia Antipolis/CNRS
Edelweiss

2. • Online communities of interest
• "Enterprise 2.0" & organizations
cross-fertilizing Web 2.0 and
Semantic Web
Context of the thesis
2

3. 3
From social tagging to folksonomies
Tags freely associated to resources …
… collected and shared on the web

4. 4
… resulting in
FOLKSONOMIES
A mass of users for a mass of resources

5. Limitations of folksonomies
5
Spelling variations of tags:
newyork = new_york = nyc

6. 6
How to turn
folksonomies ...
?
... into
topic structures (thesaurus) ?
pollution
Soil pollutions
has narrower
pollutant Energy
related related

7. 7
… without overloading users
… and by collecting
all user's expertise
into the process

8. 8
Ademe scenario
Experts
produce docs
+ tag
Archivists
centralize + tag
Public audience
read + tag
From controlled folksonomy to
structured folksonomy

9. 2. State of the art
and positioning
9

10. 10
State of the art
Automatic extraction of tag semantics:
• Similarity based on co-occurrence patterns (Specia & Motta 2007;
Catutto 2008)
• Association rule mining (Mika 2005; Hotho et al. 2006)
pollution
Soil pollutions
has narrower
pollutant Energy
related related

11. 11
State of the art
Involving users in tags structuring:
• Simple syntax to structure tags (Huyn-Kim
Bang et al. 2008)
• Crowdsourcing strategy to validate tag-
concepts mapping (Lin et al. 2010)
• Integrate ontology maturing into Social
Bookmarking tool (Braun et al. 2007)
pollution
Soil pollutions
has narrower
pollutant Energy
related related
RDF
 ? :
 Resource Description Framework
☐ Rwanda Defense Force

12. 12
State of the art
Tags and Semantic Web models
• SCOT for tags and tagging:

13. 13
State of the art
Tags and Semantic Web models
• SCOT for tags and tagging:
• MOAT (Passant & Laublet, 2008) : Raising ambiguity
by linking tags to concepts from Linked Data

14. 3. Tagging & folksonomy
enrichment models
14

15. 15
Tagging model
Tagging = linking a resource with a sign
What is tagging ?

16. 16
Tagging model
NiceTag : tagging as named graphs (Carrol 2005)
nt:TaggedResource rdfs:Resourcent:isRelatedTo
nt:TagAction(named
graph)
sioc:UserAccount
sioc:has_creator
sioc:Container
sioc:has_container
xsd:Date
dc:date

17. 17
Folksonomy enrichment
2 complementary semantic enrichment:
wind-energy
renewable
energy
windenergy
wind turbine
has broader
close match
has narrower
environment
related
Structuring tags as in a thesaurus (SKOS)
http://www.windenergy.com
nt:ManualTagAction
nt:isAbout
freddy
sioc:has_creator
delicious.com
sioc:has_container

18. 18
Tagging model
Supporting diverging points of view
car pollutionskos:related
john
agrees
paul
disagrees

19. Supporting diverging points of view
Reification of relations with named graphs
car pollutionskos:related
srtag:SingleUser
"john"
srtag:hasApproved
srtag:SingleUser
"paul"
srtag:hasRejected
srtag:TagSemanticStatement
srtag:TagStructureComputer
"r2d2"
srtag:hasProposed
19

20. 4. Going through the
folksonomy enrichment
life-cycle
20

21. ADDING TAGS
Automatic
processing
User-centric
structuring
Detect
conflicts
Global
structuring
Flat
folksonomy
Structured
folksonom
y
Folksonomy enrichment life-cycle
21

22. ADDING TAGS
Automatic
processing
User-centric
structuring
Detect
conflicts
Global
structuring
Flat
folksonomy
Structured
folksonom
y
Folksonomy enrichment life-cycle
22

23. 23
1. String-based metrics
pollution Soil pollutions
pollutantpollution
=> « pollution » related to « pollutant »
=> « pollution » broader than « soil pollutions »

24. 1. String-based
metrics results1. String-based metrics
24
close matchrelated
broader

25. 25
2. Co-occurrence patterns
Example of folksonomy

26. 26
2. Co-occurrence patterns

27. renewable energy
wind-energy
A
l
e
x
D
e
l
p
h
i
n
e
C
l
a
i
r
e
M
o
n
i
q
u
e
A
n
n
e
 Hyponym relations (broader/narrower):
« renewable energy » broader than « wind-energy »
3. User-based association
27

28. 3. User-based
association
28

29. Global results of automatic processings on Ademe data
Total with 3 automatic methods: 83027 relations for 9037 tags
29

30. ADDING TAGS
Automatic
processing
User-centric
structuring
Detect
conflicts
Global
structuring
Flat
folksonomy
Structured
folksonom
y
Folksonomy enrichment life-cycle
30

31. 31
Capturing users's contributions
Embedding structuring tasks within everyday
activity (searching e.g)

32. 32
Capturing users's contributions

33. 33
Capturing user's point of view
John
srtag:hasRejected
energie
france
skos:broader
srtag:TagSemanticStatement
Exemple:
Rejecting a relation

34. 34
Capturing user's point of view
John
srtag:hasRejected
energie
energy
skos:related
srtag:TagSemanticStatement
Exemple:
Proposing another
relation
energie
energy
skos:closeMatch
srtag:TagSemanticStatement
srtag:hasProposed

35. ADDING TAGS
Automatic
processing
User-centric
structuring
Detect
conflicts
Global
structuring
Flat
folksonomy
Structured
folksonom
y
Folksonomy enrichment life-cycle
35

36. 36
Conflict detection
environment pollution
Using rules:
IF num(narrower)/num(broader) ≥ c
THEN narrower wins
ELSE 'related' wins
narrower
John
srtag:hasApproved
Anne
srtag:hasApproved
broader
Monique
srtag:hasApproved
Delphine
srtag:hasApproved

37. 37
Conflict detection
related
broader narrower
less constrained less constrained less constrained
close match
relatedenvironment pollution
narrower
broader

38. 38
Experimentation at ADEME
Participation of 3 members at Ademe
+ 2 professionals in environment

39. Several cases of conflicting situations
Conflicting : >1 relation
per pair of tags
Approved : 1 relation,
only approved
Debatable : 1 relation,
BOTH approved and
rejected
Rejected : 1 relation, only
rejected
39

40. Several cases of conflicting situations
Distribution over
relation types :
• "closeMatch" tends
to draw a consensus
more easily than
others
•
"broader/narrower"
and "related" cause
more
debates/conflicts
40

41. Example conflict resolution
Conflicting
Conflict solver choice
debatable
rejected 41

42. ADDING TAGS
Automatic
processing
User-centric
structuring
Detect
conflicts
Global
structuring
Flat
folksonomy
Structured
folksonom
y
Folksonomy enrichment life-cycle
42

43. Helping Referent User (Ademe archivists) choose solutions to
conflicts
Reporting
43

44. 44
Global map
Choices of the referent
user (archivists at Ademe e.g.)

45. ADDING TAGS
Automatic
processing
User-centric
structuring
Detect
conflicts
Global
structuring
Flat
folksonomy
Structured
folksonom
y
Folksonomy enrichment life-cycle
45

46. Each point of view
corresponds to a layer
46

47. Enriching individual points of view
Integrating others' contributions:
1. Current user -> "Anne"
2. ReferentUser (e.g. archivists)
3. ConflictSolver (software agent)
4. Other single users
5. Automatons (metrics)
BROADER
NARROWER
RELATED
CLOSE MATCH
environnementSearch:
preoccupation environnementales
grenelle de l environnement
competences environnementales
environment
environmental
domaines environnementaux
Anne is looking for tag
"environnement"
47

48. 5. Conclusion
48

49. 49
What we do :
Help online communities
structure their tagswind-energy
renewable
energy
sustainability
wind turbine
has broader
related
has narrower
environment
related

50. • Integrating collaborative ergonomics in design of socio-
technical systems
• User interfaces : how to visualize structuring process ?
• Towards Computer Supported Argumentation
• Application to the Web at large ?
• Semantics of tags : Topic vs Concept ?
50
Dicussion

51. 51
Thank you !
freddy.limpens@inria.fr
http://www-sop.inria.fr/members/Freddy.Limpens/

52. 2010
• Monnin, A.; Limpens, F.; Gandon, F. & Laniado, D. Speech acts meets tagging: NiceTag ontology AIS SigPrag International Pragmatic Web
Conference, 2010
• Monnin, A.; Limpens, F.; Gandon, F. & Laniado, D. ,L'ontologie NiceTag : les tags en tant que graphes nommés,A. Monnin, F. Limpens, D.
Laniado, F. Gandon, EGC 2010, Atelier Web Social
• Limpens, F.; Gandon, F. & Buffa, M. Helping online communities to semantically enrich folksonomies Proceedings of the WebSci10:
Extending the Frontiers of Society On-Line, http://webscience.org, 2010
2009
• Limpens, F.; Monnin, A.; Laniado, D. & Gandon, F. NiceTag Ontology: tags as named graphs International Workshop in Social Networks
Interoperability, ASWC09, 2009
• Limpens, F.; Gandon, F. & Buffa, M. Sémantique des folksonomies : structuration collaborative et assistée Ingénierie des Connaissances,
2009
• Limpens, F.; Gandon, F. & Buffa, M. Collaborative semantic structuring of folksonomies (short article) IEEE/WIC/ACM Int. Conf. on Web
Intelligence, 2009
• Erétéo, G.; Buffa, M.; Gandon, F.; Leitzelman, M. & Limpens, F. Leveraging Social data with Semantics W3C Workshop on the Future of
Social Networking, Barcelona., 2009
• Henri, F.; Charlier, B. & Limpens, F. Understanding and Supporting the Creation of More Effective PLE Int. Conf. on Information
Resources Management, Dubai, 2009
2008
• Henri, F.; Charlier, B. & Limpens, F. Understanding PLE as an Essential Component of the Learning Process World Conf. on Educational
Multimedia, Hypermedia & Telecommunications, ED-Media, Vienna, Austria, 2008
• Limpens, F.; Gandon, F. & Buffa, M. Rapprocher les ontologies et les folksonomies pour la gestion des connaissances partagées : un Etat
de l'art Proc. 19èmes journées francophones d'Ingénierie des Connaissances, Nancy, 2008
• Limpens, F.; Gandon, F. & Buffa, M. Bridging Ontologies and Folksonomies to Leverage Knowledge Sharing on the Social Web: a Brief
Survey Proc. 1st International Workshop on Social Software Engineering and Applications (SoSEA),
http://www-sop.inria.fr/members/Freddy.Limpens/?q=biblio
52
Personal publications

53. 53

54. 54
Positioning
Computed
Tag similarity
Tag-Concept
mapping
Users'
contrib.
Sem-Web
formalism
Multi-points
of view
Angeletou et al.
(2008)
✓ ✓ ✓
Huynh-Kim Bang
et al. (2008)
✓ ✓
Passant &
Laublet(2008)
✓ ✓ ✓
Lin & Davis
(2010)
✓ ✓ ✓ ✓
Braun et al.
(2007)
✓ ✓
Our approach ✓ partly ✓ ✓ ✓

55. 55
Tagging model
Specifying the
Tagged Resource with IRW
(Halpin & Pressuti 2009)
nt:TaggedResourc
e
rdfs:Resourc
e
nt:isRelatedTo
nt:TagAction(named
graph)
nt:TaggedResource
Information resource
vs Non-Information resource,
etc.
irw:Resource
irw:Information
Resource
irw:Non
Information
Resource
≡

56. 56
Tagging model
No constraints on the model
of the sign used to tag
nt:TaggedResourc
e
rdfs:Resourc
e
nt:isRelatedTo
nt:TagAction(named
graph)
nt:TaggedResource
http:geonames.org/2990440
nt:isRelatedTo
scot:Tag
:)
skos:Concept
nt:isRelatedTo
nt:isRelatedTo
nt:isRelatedTo
nt:isRelatedTo
moat:Tag moat:hasMeaning

57. 57
Tagging model
Typing the relation to reflect
on pragmatics of use of tags
nt:TaggedResourc
e
rdfs:Resourc
e
nt:isRelatedTo
nt:TagAction(named
graph)

58. 58
Tagging model
Typing the named graphs
for additional dimensions
of tagging
nt:TaggedResourc
e
rdfs:Resourc
e
nt:isRelatedTo
nt:TagAction(named
graph)

59. 59
Tagging model
Example of a tagging in delicious
http://www.windenergy.com
nt:ManualTagAction
nt:isAbout
scot:Tag
"wind-energy"
freddy
sioc:has_creator
delicious.com
sioc:has_container