Se ha denunciado esta presentación.
Se está descargando tu SlideShare. ×

Wimmics Research Team 2015 Activity Report

Anuncio
Anuncio
Anuncio
Anuncio
Anuncio
Anuncio
Anuncio
Anuncio
Anuncio
Anuncio
Anuncio
Anuncio

Eche un vistazo a continuación

1 de 33 Anuncio

Wimmics Research Team 2015 Activity Report

Descargar para leer sin conexión

Extract of the activity report of the Wimmics joint research team between Inria Sophia Antipolis - Méditerranée and I3S (CNRS and Université Nice Sophia Antipolis). Wimmics stands for web-instrumented man-machine interactions, communities and semantics. The team focuses on bridging social semantics and formal semantics on the web.

Extract of the activity report of the Wimmics joint research team between Inria Sophia Antipolis - Méditerranée and I3S (CNRS and Université Nice Sophia Antipolis). Wimmics stands for web-instrumented man-machine interactions, communities and semantics. The team focuses on bridging social semantics and formal semantics on the web.

Anuncio
Anuncio

Más Contenido Relacionado

Presentaciones para usted (20)

Similares a Wimmics Research Team 2015 Activity Report (20)

Anuncio

Más de Fabien Gandon (18)

Más reciente (20)

Anuncio

Wimmics Research Team 2015 Activity Report

  1. 1. WIMMICSWeb-instrumented man-machine interactions, communities and semantics     Fabien GANDON http://fabien.info
  2. 2. SOPHIA TEAM  Inria  CNRS  University of Nice Inria Lille - Nord Europe (2008) Inria Saclay – Ile-de-France (2008) Inria Nancy – Grand Est (1986) Inria Grenoble – Rhône- Alpes (1992) Inria Sophia Antipolis Méditerranée (1983) Inria Bordeaux Sud-Ouest (2008) Inria Rennes Bretagne Atlantique (1980) Inria Paris-Rocquencourt (1967) Montpellier Lyon Nantes Strasbourg Center Branch Pau I3S
  3. 3. CHALLENGE to bridge social semantics and formal semantics on the Web
  4. 4. MULTI-DISCIPLINARY TEAM  50 members (2015)  14 nationalities  1 DR, 3 Professors  3CR, 4 Assistant professors  1 SRP DR/Professors:  Fabien GANDON, Inria, AI, KR, Semantic Web, Social Web  Nhan LE THANH, UNS, Logics, KR, Emotions  Peter SANDER, UNS, Web, Emotions  Andrea TETTAMANZI, UNS, AI, Logics, Agents, CR/Assistant Professors:  Michel BUFFA, UNS, Web, Social Media  Elena CABRIO, UNS, NLP, KR, Linguistics  Olivier CORBY, Inria, KR, AI, Sem. Web, Programming, Graphs  Catherine FARON-ZUCKER, UNS, KR, AI, Semantic Web, Graphs  Alain GIBOIN, Inria, Interaction Design, KE, User & Task models  Isabelle MIRBEL, UNS, Requirements, Communities  Serena VILLATA, CNRS, AI, Argumentation, Licenses, Rights Inria Starting Position: Alexandre MONNIN, Philosophy, Web
  5. 5. RESEARCH CHALLENGES 1. user & interaction design 2. communities & social networks 3. linked data & semantic Web 4. reasoning & analyzing
  6. 6. RESEARCH CHALLENGES 1. user & interaction design 2. communities & social networks 3. linked data & semantic Web 4. reasoning & analyzing How do we improve our interactions with a semantic and social Web ? • capture and model the users' characteristics? • represent and reason with the users’ profiles? • adapt the system behaviors as a result? • design new interaction means? • evaluate the quality of the interaction designed? 
  7. 7. RESEARCH CHALLENGES 1. user & interaction design 2. communities & social networks 3. linked data & semantic Web 4. reasoning & analyzing How can we manage the collective activity on social media? • analyze the social interaction practices and the structures in which these practices take place? • capture the social interactions and structures? • formalize the models of these social constructs? • analyze & reason on these models of social activity? 
  8. 8. RESEARCH CHALLENGES 1. user & interaction design 2. communities & social networks 3. linked data & semantic Web 4. reasoning & analyzing What are the needed schemas and extensions of the semantic Web formalisms for our models? • formalisms best suited for the models of the challenges 1 & 2 ? • limitations and extensions of existing formalisms? • missing schemas, ontologies, vocabularies? • links and combinations of existing formalisms? 
  9. 9. RESEARCH CHALLENGES 1. user & interaction design 2. communities & social networks 3. linked data & semantic Web 4. reasoning & analyzing What are the algorithms required to analyze and reason on the heterogeneous graphs we obtained? • analyze graphs of different types and their interactions? • support different graph life-cycles, calculations and characteristics? • assist different tasks of our users? • design the Web architecture to deploy this? 
  10. 10. METHODS AND TOOLS 1. user & interaction design 2. communities & social networks 3. linked data & semantic Web 4. reasoning & analyzing      G2 H2  G1 H1 < Gn Hn
  11. 11. METHODS AND TOOLS 1. user & interaction design 2. communities & social networks 3. linked data & semantic Web 4. reasoning & analyzing  • user models, personas, emotion capture • mockups, evaluation campaigns • KB interaction (context, Q&A, exploration, …)     G2 H2  G1 H1 < Gn Hn
  12. 12. METHODS AND TOOLS 1. user & interaction design 2. communities & social networks 3. linked data & semantic Web 4. reasoning & analyzing   • user models, personas, emotion capture • mockups, evaluation campaigns • KB interaction (context, Q&A, exploration, …) • collective personas, coordinative artifacts • community detection, labelling • argumentation theory, sentiment analysis    G2 H2  G1 H1 < Gn Hn
  13. 13. METHODS AND TOOLS 1. user & interaction design 2. communities & social networks 3. linked data & semantic Web 4. reasoning & analyzing    • user models, personas, emotion capture • mockups, evaluation campaigns • KB interaction (context, Q&A, exploration, …) • collective personas, coordinative artifacts • community detection, labelling • argumentation theory, sentiment analysis • ontology-based knowledge representation • formalisms: typed graphs, uncertainty • knowledge extraction, data translation   G2 H2  G1 H1 < Gn Hn
  14. 14. METHODS AND TOOLS 1. user & interaction design 2. communities & social networks 3. linked data & semantic Web 4. reasoning & analyzing     • user models, personas, emotion capture • mockups, evaluation campaigns • KB interaction (context, Q&A, exploration, …) • collective personas, coordinative artifacts • community detection, labelling • argumentation theory, sentiment analysis • ontology-based knowledge representation • formalisms: typed graphs, uncertainty • knowledge extraction, data translation • graph querying, reasoning, transforming • induction, propagation, approximation • explanation, tracing, control, licensing, trust
  15. 15. RESULTS 2013-2015 1. user & interaction design 2. communities & social networks 3. linked data & semantic Web 4. reasoning & analyzing     • e.g. DiscoveryHub, PRISSMA, QAKiS [IJCAI, WI, Semantics, ESWC, Hypertext, IJSWIS, …] • e.g. OCKTOPUS, WikiNEXT, SEEMPAD [AI, CHI, ECAI, WI, COMMA, ASONAM, IAT, SAC, …] • e.g. L4LOD, S4AC, Ratio4TA, Dbpedia.fr [ECAI, IJCAI, LREC, AAMAS, RuleML, WebIST, …] • e.g. CORESE, Licentia, DiscoveryHub, PRISSMA [ISWC, EKAW, KCAP, WI, ESWC, Hypertext, ICAIL, …]
  16. 16. SEARCHING  exploratory search  question-answering
  17. 17. SEARCHING  exploratory search  question-answering DBPEDIA.FR (extraction, end-point) 180 000 000 triples models Web architecture
  18. 18. SEARCHING  exploratory search  question-answering DBPEDIA.FR (extraction, end-point) 180 000 000 triples DISCOVERYHUB.CO semantic spreading activation new evaluation protocol
  19. 19. SEARCHING  exploratory search  question-answering DBPEDIA.FR (extraction, end-point) 180 000 000 triples DISCOVERYHUB.CO QAKiS.ORG semantic spreading activation new evaluation protocol [D:Work], played by [R:Person] [D:Work] stars [R:Person] [D:Work] film stars [R:Person] starring(Work, Person) linguistic relational pattern extraction named entity recognition similarity based SPARQL generation select * where { dbpr:Batman_Begins dbp:starring ?v . OPTIONAL {?v rdfs:label ?l filter(lang(?l)="en")} }
  20. 20. MODELING USERS  individual context  social structures
  21. 21. MODELING USERS  individual context  social structures PRISSMA prissma:Context 0 48.86034 -2.337599 200 geo:lat geo:lon prissma:radius 1 :museumGeo prissma:Environment 2 { 3, 1, 2, { pr i ssma: poi } } { 4, 0, 3, { pr i ssma: envi r onment } } :atTheMuseum error tolerant graph edit distance context ontology
  22. 22. MODELING USERS  individual context  social structures PRISSMA prissma:Context 0 48.86034 -2.337599 200 geo:lat geo:lon prissma:radius 1 :museumGeo prissma:Environment 2 { 3, 1, 2, { pr i ssma: poi } } { 4, 0, 3, { pr i ssma: envi r onment } } :atTheMuseum error tolerant graph edit distance context ontology OCKTOPUS tag, topic, user distribution tag and folksonomy restructuring with prefix trees
  23. 23. MODELING USERS  individual context  social structures PRISSMA prissma:Context 0 48.86034 -2.337599 200 geo:lat geo:lon prissma:radius 1 :museumGeo prissma:Environment 2 { 3, 1, 2, { pr i ssma: poi } } { 4, 0, 3, { pr i ssma: envi r onment } } :atTheMuseum error tolerant graph edit distance context ontology OCKTOPUS tag, topic, user distribution tag and folksonomy restructuring with prefix trees EMOCA&SEEMPAD emotion detection & annotation
  24. 24. QUERY & INFER  graph rules and queries  deontic reasoning  induction
  25. 25. QUERY & INFER  graph rules and queries  deontic reasoning  induction CORESE  & G2 H2  & G1 H1 < Gn Hn abstract graph machine STTL
  26. 26. QUERY & INFER  graph rules and queries  deontic reasoning  induction CORESE  & G2 H2  & G1 H1 < Gn Hn RATIO4TA predict & explain abstract graph machine STTL
  27. 27. QUERY & INFER  graph rules and queries  deontic reasoning  induction CORESE INDUCTION  & G2 H2  & G1 H1 < Gn Hn RATIO4TA predict & explain find missing knowledge abstract graph machine STTL
  28. 28. QUERY & INFER  graph rules and queries  deontic reasoning  induction CORESE LICENTIA INDUCTION  & G2 H2  & G1 H1 < Gn Hn RATIO4TA predict & explain find missing knowledge license compatibility and composition abstract graph machine STTL
  29. 29. ACHIEVEMENTS • publications • awards • visibility • 9 Ph.D. theses defended • multidisciplinary publication • best paper awards: ESWC 2013 ; EEE/WIC/ACM IAT 2014 ; IEEE Cognitive Infocommunications ; IEEE BDAS 2014 ; IC2015 • PC of major journals and conferences • General Chair ESWC 2015, PC chair ESWC 2014, ...
  30. 30. COLLABORATIONS • collaborative projects (7) • industrial contracts (6) • scholarships (8) + MIREL
  31. 31. DIFFUSION / TRANSFER • education, training • industrial transfer • two MOOCS (HTML5 EN 100K, Semantic Web FR 4K) • important teaching activity • W3C participation (AC Rep, several WG) • 2 Carnot projects with SMEs • first ANR LabCom on digital sciences joint Lab Wimmics-Viseo • spin-off to industrialize research results one of the first software cooperatives
  32. 32. FUTURE • Linked Data & Web diversity • Artificial Web intelligence • Human-Data Web Interactions • Web-augmented interactions • coupling AI and distributed AI with the Web • knowledge representation & extraction on the Web • incremental & linked formalizations • argumentation mining & theory • textual entailment & LOD-based NLP • participatory design and evaluation • natural language question-answering and dialogue • visual analytics for linked data • architecture & philosophy of the Web
  33. 33. WIMMICSbridging social semantics and formal semantics on the Web. epistemic communitieslinked data usages and introspection contributions and traces

×