1. A WEB LINKING
ALL KINDS OF INTELLIGENCE
Fabien GANDON
@fabien_gandon
http://fabien.info
  
Vice Head of Science of Inria Sophia Antipolis
Head of the Wimmics Lab. (Inria, UCA, CNRS, I3S)
W3C Advisory Committee representative for Inria
Director of QWANT-Inria Joint Laboratory
Leader of the Convention Ministry of Culture - Inria

2. the Web: this place where invisible brontobytes graze furiously

3. AI & IA
Web as the focal point of two fields born in the 50s
AI for Artificial Intelligence (McCarthy et al., 1955)

4. AI & IA
Web as the focal point of two fields born in the 50s
AI for Artificial Intelligence (McCarthy et al., 1955)
IA for Intelligence Amplification (Ashby, 1956) and
Intelligence Augmentation (Engelbart, 1962)

5. the Web as a universal space to link…
data

6. [TimBL, 94]

7. a Web approach to data publication
???...« http://fr.dbpedia.org/resource/Paris »

8. a Web approach to data publication
HTTP URI
GET

9. a Web approach to data publication
HTTP URI
GET
HTML, …

10. a Web approach to data publication
HTTP URI
GET
HTML,RDF, XML,…

11. The MUC18 protein at UniProt
http://www.uniprot.org/uniprot/P43121

12. linked open data(sets) cloud on the Web
0
200
400
600
800
1000
1200
1400
01/05/2007 08/10/2007 07/11/2007 10/11/2007 28/02/2008 31/03/2008 18/09/2008 05/03/2009 27/03/2009 14/07/2009 22/09/2010 19/09/2011 30/08/2014 26/01/2017
number of linked open datasets on the Web

15. http://dbpedia.org/resource/Sophia_Antipolis

16. the Web as a universal space to link…
data, schemata

17. automated deduction
all birds can fly
all penguins are birds
so ...

18. PIPE : 0.9143
automated classification

19. OWL in one…
algebraic properties
disjoint properties
qualified cardinality
1..1
!
individual prop. neg
chained prop.


enumeration
intersection
union
complement
 disjunction
restriction!
cardinality
1..1
equivalence
[>18]
disjoint union
value restriction
keys
…

20. schemata on the Web

21. QUERY & INFER
 graph rules and queries
 deontic reasoning
 induction
CORESE
 &
G2 H2
 &
G1 H1
<
Gn Hn
abstract graph machine
STTL
[Corby, Faron-Zucker et al.]

22. QUERY & INFER
 graph rules and queries
 deontic reasoning
 induction
CORESE
 &
G2 H2
 &
G1 H1
<
Gn Hn
RATIO4TA
predict &
explain
abstract graph machine
STTL
[Hasan et al.]
[Corby, Faron-Zucker et al.]

23. 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
[Hasan et al.]
[Tettamanzietal.]
[Corby, Faron-Zucker et al.]

24. QUERY & INFER
 graph rules and queries
 deontic reasoning
 induction
CORESE
LICENTIA
INDUCTION
 &
G2 H2
 &
G1 H1
<
Gn Hn
RATIO4TA
predict &
explain
find missing
knowledge
deontic reasoning, license
compatibility and composition
abstract graph machine
STTL
[Hasan et al.]
[Tettamanzietal.]
[Villata et al.]
[Corby, Faron-Zucker et al.]

25. URI, IRI, URL, HTTP URI
DATA AND SCHEMATA ON THE WEB: A GROWING STACK
JSON
RDF
JSON LD
N-Triple
N-Quad
Turtle/N3
TriG
RDFS
OWL
SPARQL
XML
HTML
RDF XML
HTTP
Linked Data
CSV-LD R2RML
GRDDL
RDFa
SHACL
LDP

26. the Web as a universal space to link…
data, schemata, programs

28. deduce data

model, schemas, ontologies, ...
data data
15% progress

29. learn data
embeddings, parameters, configurations, …
data data
30% progress

30. sum intelligence

model, schemas, ontologies, ...
embeddings, parameters, configurations, …
data data
45% progress

31. combine intelligence
model, schemas, ontologies, ...
embeddings, parameters, configurations, …
data

60% progress

32. remotely combine
model, schemas, ontologies, …
embeddings, parameters, configurations,…

Web
75% progress

33. deeply combine
data, knowledge, model, schemas, ontologies, …
data, knowledge, embeddings, parameters, configurations,…

Web
90% progress

34. combining AIs on the Web
data, knowledge, model, schemas, ontologies, …
data, knowledge, embeddings, parameters, configurations,…

Web
100% progress

35. the Web as a global blackboard
for artificial intelligence

36. Smarter Cities – IBM Dublin
[Lécué, 2015]

37. Smarter Cities – IBM Dublin
[Lécué, 2015]

38. ALOOF: robots learning by reading on the Web
 First Object Relation Knowledge Base: 46212 co-mentions, 49 tools, 14 rooms, 101
“possible location” relations, 696 tuples <entity, relation, frame>
 Evaluation: 100 domestic instruments, 20 rooms, 2000 crowdsourcing judgements
 Shared between robots through a shared Web knowledge base
Annie cuts the bread in the kitchen with her knife dbp:Knife aloof:Location dbp:Kitchen
[Cabrio, Basile
et al. 2017]

39. PREDICT HOSPITALIZATION
 Physician’s records classification
in order to predict hospitalization
[Gazzotti, Faron et al. 2017]
Sexe Date Cause CISP2 ... History Observations
H 25/04/2012 vaccin-antitétanique A44 ... Appendicite EN CP - Bon état général -
auscult pulm libre; bdc
rég sans souffle - tympans
ok-
Element Number
Patients
Consultations
Past medical history
Biometric data
Semiotics
Diagnosis
Row of prescribed drugs
Symptoms
Health care procedures
Additional examination
Paramedical prescription
Observations/notes
55 823
364 684
187 290
293 908
250 669
117 442
847 422
23 488
11 850
871 590
17 222
56 143

40. PREDICT HOSPITALIZATION
 Physician’s records classification
in order to predict hospitalization
 Augment data with structured
knowledge and study impact on
different prediction methods
[Gazzotti, Faron et al. 2017]
Sexe Date Cause CISP2 ... History Observations
H 25/04/2012 vaccin-antitétanique A44 ... Appendicite EN CP - Bon état général -
auscult pulm libre; bdc
rég sans souffle - tympans
ok-
Element Number
Patients
Consultations
Past medical history
Biometric data
Semiotics
Diagnosis
Row of prescribed drugs
Symptoms
Health care procedures
Additional examination
Paramedical prescription
Observations/notes
55 823
364 684
187 290
293 908
250 669
117 442
847 422
23 488
11 850
871 590
17 222
56 143
(1)
(2)

41. MonaLIA
 reason & query on RDF metadata to build
balanced, unambiguous, labelled training sets.
350 000 images
of artworks
RDF metadata based
on external thesauri
Joconde database from French museums
[Bobasheva et al. 2017]

42. MonaLIA
 reason & query on RDF metadata to build
balanced, unambiguous, labelled training sets.
 transfer learning & CNN classifiers on targeted
categories (topics, techniques, etc.)
 reason & query RDF metadata of results to
address silence, noise and explain
350 000 images
of artworks
RDF metadata based
on external thesauri
Joconde database from French museums
(1)
(2)
[Bobasheva et al. 2017]
animal 
bird ?
painting 

43. WEB EDGE AI
 Edge AI directly in the browser
 Web APIs, models, protocols,…
[WebML @ W3C]

44. the Web as a universal space to link…
data, schemata, programs, intelligence

45. 0
500000
1000000
1500000
2000000
2500000
3000000
3500000
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50
Wikipedia editors / # acts of edition, 2012

46. 0
500000
1000000
1500000
2000000
2500000
3000000
3500000
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50
Human Wikipedia editors / # acts of edition, 2012

47. emotional (artificial) intelligence
•emotion felt
•emotion expressed
•opinion
•strong language
•etc.

48. Toward a Web of Things

49. Connected Animals, Animal-computer interaction (ACI)
Herdsourcing: monitoring collective animal behavior

50. IMAG_NE

51. the Web as a global blackboard
for artificial intelligence
all kinds of

52. WIMMICSVice Head of Science of Inria Sophia Antipolis - Méditerranée
Head of the Wimmics Lab. (Inria, UCA, CNRS, I3S)
W3C Advisory Committee representative for Inria
Director of QWANT-Inria Joint Laboratory
Leader of the Convention Ministry of Culture – Inria
Web-instrumented man-machine interactions, communities and semantics
Fabien Gandon - @fabien_gandon - http://fabien.info
he who controls metadata, controls the web
and through the world-wide web many things in our world.
http://bit.ly/wimmics-papers   