Freddy Limpens: From folksonomies to ontologies: a socio-technical solution

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

• Online communities of interest

• "Enterprise 2.0" & organizations

cross-fertilizing Web 2.0 and Semantic Web

Context of the thesis

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From social tagging to folksonomies

Tags freely associated to resources …

… collected and shared on the web

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… resulting in

FOLKSONOMIES

A mass of users for a mass of resources

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Limitations of folksonomies

Spelling variations of tags:

newyork = new_york = nyc

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How to turn folksonomies ...

?... into

topic structures (thesaurus) ?

pollution

Soil pollutions

has narrower

pollutant Energy

related related

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… without overloading users

… and by collectingall user's expertiseinto the process

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Ademe scenario

Expertsproduce docs

+ tagArchivists

centralize + tag

Public audienceread + tag

From controlled folksonomy to structured folksonomy

2. State of the artand positioning

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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

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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

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State of the art

Tags and Semantic Web models• SCOT for tags and tagging:

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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

3. Tagging & folksonomy enrichment models

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Tagging model

Tagging = linking a resource with a sign

What is tagging ?

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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

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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

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Tagging model

Supporting diverging points of view

car pollutionskos:related

john

agrees

paul

disagrees

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

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4. Going through the folksonomy enrichment life-cycle

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ADDING TAGS

Automatic processing

User-centricstructuring

Detect conflicts

Globalstructuring

Flat folksonomy

Structured folksonom

y

Folksonomy enrichment life-cycle

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ADDING TAGS



Detect conflicts

Globalstructuring

Flat folksonomy


y


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1. String-based metrics

pollution Soil pollutions

pollutantpollution

=> « pollution » related to « pollutant »

=> « pollution » broader than « soil pollutions »

1. String-based metrics results1. String-based metrics

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close matchrelated

broader

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2. Co-occurrence patterns

Example of folksonomy

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2. Co-occurrence patterns

renewable energywind-energy

Alex

Delphine

Claire

Monique

Anne

Hyponym relations (broader/narrower):

« renewable energy » broader than « wind-energy »

3. User-based association

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3. User-based association

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Global results of automatic processings on Ademe dataTotal with 3 automatic methods: 83027

relations for 9037 tags

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ADDING TAGS



Detect conflicts

Globalstructuring

Flat folksonomy


y


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Capturing users's contributions

Embedding structuring tasks within everyday activity (searching e.g)

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Capturing users's contributions

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Capturing user's point of view

John

srtag:hasRejectedenergie

france

skos:broader


Exemple:Rejecting a relation

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Capturing user's point of view

John

srtag:hasRejectedenergie

energy

skos:related


Exemple:Proposing another

relation

energie

energy

skos:closeMatch


srtag:hasProposed

ADDING TAGS



Detect conflicts

Globalstructuring

Flat folksonomy


y


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Conflict detection

environment pollution

Using rules:

IF num(narrower)/num(broader) ≥ cTHEN narrower winsELSE 'related' wins

narrower

John

srtag:hasApproved

Annesrtag:hasApproved

broader

Monique

srtag:hasApproved

Delphinesrtag:hasApproved

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Conflict detection

related

broader narrower

less constrained less constrained less constrained

close match

relatedenvironment pollutionnarrower

broader

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Experimentation at ADEME

Participation of 3 members at Ademe + 2 professionals in environment

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

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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

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Example conflict resolutionConflictingConflict solver choicedebatablerejected

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ADDING TAGS



Detect conflicts

Globalstructuring

Flat folksonomy


y


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Helping Referent User (Ademe archivists) choose solutions to conflicts

Reporting

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Global map

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

ADDING TAGS



Detect conflicts

Globalstructuring

Flat folksonomy


y


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pollutants

pollution

environment

environment

pollutants

pollution

narrower

narrower

Paul

environment

pollution

narrower

John

environment

pollution

related

Referent

pollutants

narrower

Each point of view corresponds to a layer

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Enriching individual points of view

Integrating others' contributions:1. Current user -> "Anne"2. ReferentUser (e.g. archivists)3. ConflictSolver (software agent)4. Other single users5. 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"

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5. Conclusion

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What we do :

Help online communities

structure their tagswind-energy

renewable energy

sustainability

wind turbine

has broader

related

has narrower

environment

related

• 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 ?

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Dicussion

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Thank you !

[email protected]

http://www-sop.inria.fr/members/Freddy.Limpens/



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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, 20102009• 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, 20092008 • 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

Personal publications





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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 ✓ ✓ ✓

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Tagging model

Specifying the Tagged Resource with IRW

(Halpin & Pressuti 2009)



nt:TaggedResource

Information resource vs Non-Information resource,

etc.

irw:Resource

irw:InformationResource

irw:NonInformation

Resource

≡

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Tagging model

No constraints on the model of the sign used to tag nt:TaggedResource rdfs:Resourcent:isRelatedTo


nt:TaggedResource

http:geonames.org/2990440nt:isRelatedTo

scot:Tag

:)

skos:Concept

nt:isRelatedTo

nt:isRelatedTo

nt:isRelatedTo

nt:isRelatedTo

moat:Tag moat:hasMeaning

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Tagging model

Typing the relation to reflect on pragmatics of use of tags nt:TaggedResource rdfs:Resourcent:isRelatedTo


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Tagging model

Typing the named graphs for additional dimensions of tagging



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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

Technology

Freddy Limpens: From folksonomies to ontologies: a socio-technical solution