A full lifecycle for the semantic enrichment of folksonomies

Un cycle de vie complet pour mantiquedes folksonomies

A full lifecycle for the semantic enrichment of folksonomies

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E G C 2 0 1 1 – B R E S T

2 5 - 2 8 . 0 1 . 2 0 1 1

Freddy Limpens, Fabien Gandon

(Edelweiss, INRIA Sophia Antipolis)

Michel Buffa

(Kewi-I3S, UNSA-CNRS)

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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

Limitations of folksonomies

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Spelling variations of tags:

newyork= new_york = nyc

Limitations of folksonomies

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Ambiguityof tags

… or in Texas, USA ?

… in France ?

paris

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How to turn folksonomies ...

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... intotopic 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

1. State of the art

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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)

pollution

Soil pollutions

has narrower

pollutant Energy

related related

RDF

? : Resource Description Framework☐ Rwanda Defense Force

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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; Hothoet al. 2006)

pollution

Soil pollutions

has narrower

pollutant Energy

related related

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State of the art

Tags and Semantic Web models

TAGS + SCOT + SIOC + FOAF for tags and tagging :

tags:Tagging#11111

sioc:Itemhttp://www.windenergy.com

tags:taggedResource

scot:Tag#wind-energy

tags:associatedTag

foaf:Agent#freddy.limpens

tags:taggedBy

2. Tagging &folksonomyenrichment models

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Tagging model

Tagging = linkingaresourcewith asign

What is a tagging ?

"nature"

picture shows "nature"

(1) (2) (3)

place located l:england

editing makes me : )

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Tagging model

NiceTag(Monnin et al, 2010):

Tagging as named graphs*

*Carrolet al. (2005)

nt:TaggedResourcehttp://www.windenergy.com

nt:ManualTagAction (named graph)

nt:isAboutscot:Tag

#wind-energy

sioc:UserAccountfreddy

sioc:has_creator

sioc:Containerdelicious.com

sioc:has_container

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Folksonomy enrichment

2 complementary semantic enrichment:

http://www.windenergy.com

nt:ManualTagAction

nt:isAbout wind-energy

renewable energy

windenergy

wind turbine

has broader

close match

has narrower

environment

related

Structuring tags as in a thesaurus (SKOS)

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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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Ademe scenario

Expertsproduce docs

+ tagArchivists

centralize + tag

Public audienceread + tag

Life-cycle grounded on usage analysis

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Ademe’s dataset

Delicious TheseNet Cadic

WhatBookmarks of usersof tag "ademe"

Keywords for Ademe'sPhDproje

cts

Archivistsindexinglexicon

# tags 1015 6583 1439

# resources 196 1425 4675

# tagging

(1R - 1T - 1U)3015 10160 25515

# users 812 1425 1

3. Going through the folksonomy enrichment life-cycle

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ADDING TAGS

Automatic processing

User-centricstructuring

Detectconflicts

Globalstructuring

Flatfolksonomy

Structuredfolksonomy

Folksonomy enrichment life-cycle

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ADDING TAGS



Detectconflicts

Globalstructuring

Flatfolksonomy



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Automaticprocessing

1. String-based

2. Co-occurrence patterns

3. User-based associations

Flatfolksonomy

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3 methodsto automaticallyextract tags semantics

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1. String-based metrics

pollution Soil pollutions

pollutantpollution

=> « pollution » related to « pollutant »

=> « pollution » broaderthan« soil pollutions »

1. String-based

metrics results1. String-based metrics

25results on full dataset

tags from experts

tags fromarchivstsclose matchrelated

broader

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Example of folksonomy

cc

ecology energy wind turbine sustainability housing

ecology 0 1 1 3 1

energy 1 0 2 4 3

wind turbine 1 2 0 1 1

sustainability 3 4 1 0 4

housing 1 3 1 4 0

IFσ> 0.85 => "energy" related "sustainability"


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Cadicdataset

renewableenergywind-energy

Alex

Delphine

Claire

Monique

Anne

Hyponym relations (broader/narrower):

« renewableenergy »broaderthan« wind-energy »

3. User-based association

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3. User-based association

THESENET dataset

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Global results of automatic processings

Total with 3 automatic methods: 83027 relations for 9037 tags

– 68633 related

– 11254hyponym

– 3193 spelling variants

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?

Computed relations are not always accurate

ADDING TAGS



Detectconflicts

Globalstructuring

Flatfolksonomy



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Firefox extension SRTAgEditor

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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



Detectconflicts

Globalstructuring

Flatfolksonomy



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Conflict detection

environment pollution

Using rules:

IFnum(narrower)/num(broader) ≥ cTHENnarrowerwinsELSErelatedwins

narrower

John

srtag:hasApproved

Anne

srtag:hasApproved

broader

Monique

srtag:hasApproved

Delphine

srtag:hasApproved

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Conflict detection

related

broader narrower

less constrained less constrained less constrained

close match

relatedenvironment pollutionnarrower

broader

ConflictingConflictSolverchoicedebatablerejected

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Conflict detection

Experimentationat ADEME

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ADDING TAGS



Detectconflicts

Globalstructuring

Flatfolksonomy



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Global map

Includes all points of view, highlightsconflicts + consensuses

Referent choices

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Choices of the referent user (archivistsatAdemee.g.)

ADDING TAGS



Detectconflicts

Globalstructuring

Flatfolksonomy



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Each point of viewcorresponds to a layer

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Enriching individual points of view

Integratingothers' contributions:1. Current user -> "Anne"2. ReferentUser (e.g. archivists)3. ConflictSolver (software agent)4. Otherindividualusers5. Automatons (metrics)

BROADER

NARROWER

RELATED

CLOSE MATCH

environnementSearch:

preoccupation environnementales

grenelle de lenvironnement

competences environnementales

environment

environmental

domainesenvironnementaux

Anne is looking for resources tagged "environnement"

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Algorithmbased on random labelspropagation

(Raghavan et al., 2007):

Why not using tags instead and theirsemantic relations ?

Application to communitydetection (Érétéo, 2011)

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Application to Ademe'ssocial network :

•linking 1 tag to each user (the mostoftenused one)

•whentwousers are linkedAND their tags are related=>mergethem

•with 9200 tags => group users in 30 communities


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Result for "biggest" tags :

1. pollution

2. développement durable

3. énergie

4. chimie

5. pollution de l'air

6. métaux

7. biomasse

8. déchets

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

An approach to bridge tagging with Semantic Web:

Automatic processing of tags:

User interface to capture tag structuring embedded in every-day tasks

Implementation within ISICIL solution (tagging server)

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Our contributions:

• More user interfaces :

• ISICIL :test with final users Ademe and Orange labs

• Testing on other types of communities

• Temporal dimension

• Multilinguism

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Future work

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Thank you for your attention !

me : [email protected]://www-sop.inria.fr/members/Freddy.Limpens

myadvisors : Fabien Gandon : [email protected] Buffa : [email protected]

"communitydetectionguy":Guillaume Erétéo : [email protected]

ISICIL team :http://isicil.inria.fr

ANGELETOU S., SABOU M. & MOTTA E. (2008). Semantically Enriching Folksonomies with FLOR. In CISWeb Workshop at European Semantic Web Conference ESWC.

BRAUN S., SCHMIDT A., WALTER A., NAGYPÁL G. & ZACHARIAS V. (2007). Ontology maturing: a collaborative web 2.0 approach to ontology engineering. In CKC, volume 273 of CEUR Workshop Proceedings: CEURWS.org.

CATTUTO C., BENZ D., HOTHO A. & STUMME G. (2008). Semantic grounding of tag relatedness in social bookmarking systems. In Proceedings of the 7th International Conference on The Semantic Web, Berlin, Heidelberg: Springer-Verlag.

GANDONF.,BOTTOLIERV.,CORBYO.&DURVILLEP. (2007).Rdf/xml source declaration, w3c member submission. http://www.w3.org/Submission/rdfsource/.

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LIN H. & DAVIS J. (2010). Computational and crowdsourcing methods for extracting ontological structure from folksonomy. In ESWC (2), volume 6089 of Lecture Notes in Computer Science, p. 472–477: Springer.

MIKA P. (2005). Ontologies are Us: a Unified Model of Social Networks and Semantics. In ISWC, volume 3729 of LNCS, p. 522–536: Springer.

MONNIN A., LIMPENS F., GANDON F. & LANIADO D. (2010). Speech acts meet tagging: Nicetag ontology. In I-SEMANTICS ’10: Proceedings of the 6th International Conference on Semantic Systems, p. 1–10, New York, NY, USA: ACM.

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References

A full lifecycle for the semantic enrichment of folksonomies

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