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

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Freddy Limpens' presentation at PhiloWeb 2010.

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  • Giving basic of the models aimed at giving us expressivity we need
  • En couleur
  • Ajouter slide traduisantcecidansl'interfaceRefaire le graphetrauduitdansl'interface + ajouter image user "Anne"
  • Freddy Limpens: From folksonomies to ontologies: a socio-technical solution.

    1. 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. 2. • Online communities of interest • "Enterprise 2.0" & organizations cross-fertilizing Web 2.0 and Semantic Web Context of the thesis 2
    3. 3. 3 From social tagging to folksonomies Tags freely associated to resources … … collected and shared on the web
    4. 4. 4 … resulting in FOLKSONOMIES A mass of users for a mass of resources
    5. 5. Limitations of folksonomies 5 Spelling variations of tags: newyork = new_york = nyc
    6. 6. 6 How to turn folksonomies ... ? ... into topic structures (thesaurus) ? pollution Soil pollutions has narrower pollutant Energy related related
    7. 7. 7 … without overloading users … and by collecting all user's expertise into the process
    8. 8. 8 Ademe scenario Experts produce docs + tag Archivists centralize + tag Public audience read + tag From controlled folksonomy to structured folksonomy
    9. 9. 2. State of the art and positioning 9
    10. 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. 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. 12 State of the art Tags and Semantic Web models • SCOT for tags and tagging:
    13. 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. 14. 3. Tagging & folksonomy enrichment models 14
    15. 15. 15 Tagging model Tagging = linking a resource with a sign What is tagging ?
    16. 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. 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. 18 Tagging model Supporting diverging points of view car pollutionskos:related john agrees paul disagrees
    19. 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. 20. 4. Going through the folksonomy enrichment life-cycle 20
    21. 21. ADDING TAGS Automatic processing User-centric structuring Detect conflicts Global structuring Flat folksonomy Structured folksonom y Folksonomy enrichment life-cycle 21
    22. 22. ADDING TAGS Automatic processing User-centric structuring Detect conflicts Global structuring Flat folksonomy Structured folksonom y Folksonomy enrichment life-cycle 22
    23. 23. 23 1. String-based metrics pollution Soil pollutions pollutantpollution => « pollution » related to « pollutant » => « pollution » broader than « soil pollutions »
    24. 24. 1. String-based metrics results1. String-based metrics 24 close matchrelated broader
    25. 25. 25 2. Co-occurrence patterns Example of folksonomy
    26. 26. 26 2. Co-occurrence patterns
    27. 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. 28. 3. User-based association 28
    29. 29. Global results of automatic processings on Ademe data Total with 3 automatic methods: 83027 relations for 9037 tags 29
    30. 30. ADDING TAGS Automatic processing User-centric structuring Detect conflicts Global structuring Flat folksonomy Structured folksonom y Folksonomy enrichment life-cycle 30
    31. 31. 31 Capturing users's contributions Embedding structuring tasks within everyday activity (searching e.g)
    32. 32. 32 Capturing users's contributions
    33. 33. 33 Capturing user's point of view John srtag:hasRejected energie france skos:broader srtag:TagSemanticStatement Exemple: Rejecting a relation
    34. 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. 35. ADDING TAGS Automatic processing User-centric structuring Detect conflicts Global structuring Flat folksonomy Structured folksonom y Folksonomy enrichment life-cycle 35
    36. 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. 37 Conflict detection related broader narrower less constrained less constrained less constrained close match relatedenvironment pollution narrower broader
    38. 38. 38 Experimentation at ADEME Participation of 3 members at Ademe + 2 professionals in environment
    39. 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. 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. 41. Example conflict resolution Conflicting Conflict solver choice debatable rejected 41
    42. 42. ADDING TAGS Automatic processing User-centric structuring Detect conflicts Global structuring Flat folksonomy Structured folksonom y Folksonomy enrichment life-cycle 42
    43. 43. Helping Referent User (Ademe archivists) choose solutions to conflicts Reporting 43
    44. 44. 44 Global map Choices of the referent user (archivists at Ademe e.g.)
    45. 45. ADDING TAGS Automatic processing User-centric structuring Detect conflicts Global structuring Flat folksonomy Structured folksonom y Folksonomy enrichment life-cycle 45
    46. 46. Each point of view corresponds to a layer 46
    47. 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. 48. 5. Conclusion 48
    49. 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. 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. 51 Thank you ! freddy.limpens@inria.fr http://www-sop.inria.fr/members/Freddy.Limpens/
    52. 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. 53
    54. 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. 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. 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. 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. 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. 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

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