catherine roussey, researcher at cemagrefvery good introduction of ontologies used by computer science... I like the examples of what a human and what a machine do with web page.1 year ago
Ontologies in computer science and on the webPresentation Transcript
human
person
ontologies and on the web
in computer science
fabien, gandon, inria
book victor hugo
2
what is the
balance
of the project ?
3
4
5
one word, two
meanings
6
do not read
the following sign
7
too late
8
we interpret
machines don't
9
The Man Who Mistook His Wife for a Hat :
And Other Clinical Tales by Oliver W. Sacks
In his most extraordinary book, quot;one of the great clinical writers of the 20th centuryquot; (The New
York Times) recounts the case histories of patients lost in the bizarre, apparently inescapable world
of neurological disorders. Oliver Sacks's The Man Who Mistook His Wife for a Hat tells the stories
of individuals afflicted with fantastic perceptual and intellectual aberrations: patients who have
lost their memories and with them the greater part of their pasts; who are no longer able to
recognize people and common objects; who are stricken with violent tics and grimaces or who
shout involuntary obscenities; whose limbs have become alien; who have been dismissed as
retarded yet are gifted with uncanny artistic or mathematical talents.
If inconceivably strange, these brilliant tales remain, in Dr. Sacks's splendid and sympathetic telling, deeply human. They
are studies of life struggling against incredible adversity, and they enable us to enter the world of the neurologically
impaired, to imagine with our hearts what it must be to live and feel as they do. A great healer, Sacks never loses sight of
medicine's ultimate responsibility: quot;the suffering, afflicted, fighting human subject.quot;
Our rating :
Oliver Sacks
Find other books in : Neurology Psychology
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10
taxonomical
knowledge is a kind of
ontological
knowledge among others
20
part
of
CH4 C2 H6 CH3-OH C2H6-OH
…
methane ethane methanol ethanol
CO2 O3 -OH H2
-CH3 O2 H2 O
ozone
carbon dioxide dioxygen phenol water dihydrogen
methyl
C O H
carbon oxygen hydrogen
21
combine
different kinds of ontological knowledge
Organic object
Individual Limb
Cat
Hierarchical model of the shape of the human body. D. Marr and H.K. Nishihara, Representation and recognition
of the spatial organization of three-dimensional shapes, Proc. R. Soc. London B 200, 1978, 269-294).
22
ontos
to be / beings
“Jacob Lorhard's quot;Ogdoas Scholasticaquot; (1606) contains the first occurrence of
Ogdoas
the term ‘ontologia’ ” Raul Corazzon on formalontology.it
logos
discourse/science
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Ontology ontology
->
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ntology
O
a logical theory which gives an explicit,
partial account of a conceptualization i.e. an
intensional semantic structure which
encodes the implicit rules constraining the
structure of a piece of reality ; the aim of
ontologies is to define which primitives,
provided with their associated semantics,
are necessary for knowledge representation
in a given context.
[Gruber, 1993] [Guarino & Giaretta, 1995] [Bachimont, 2000]
25
coverage
extent to which the primitives mobilized by
the scenarios are covered by the ontology.
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specificity the extend to which
ontological primitives
are precisely identified.
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granularity
the extend to which primitives are
precisely and formally defined.
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formality
the extend to which primitives are
described in a formal language.
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ontology
knowledge-based
system
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e.g. students have marks
s s
marks are floats ≤ 20 and ≥ 0
s
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ontology
knowledge-based
system
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e.g. Stephan had a mark of 15.5
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knowledge base
ontology
knowledge-based
system
rules
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e.g. if a student has at least one mark
below 8 then he fails the year
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knowledge base
ontology
knowledge-based
system
rules verification
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e.g. the total number of marks for a course
must be equal to the total number of
students attending the course
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knowledge base
ontology
knowledge-based
system
rules verification explanation
etc.
38
languages
to formalize ontologies
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(define-class human (?human)
:def (animal ?human))
example
40 subsumption in frames
(defprimconcept MALE)
(defprimconcept FEMALE)
(disjoint MALE FEMALE)
example
41 disjoint classes in description logics
[Concept: Director]->(Def)->
[LambdaExpression:
[Person: λ] ->(Manage) -> [Group]]
example
42 defined class in conceptual graphs
W3C®
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RDF is a triple model i.e. every
piece of knowledge is broken down into
( subject , predicate , object )
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doc.html has for author Fabien
and has for theme Music
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RDFS provides primitives for
S
lightweight ontologies
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<Class rdf:ID=quot;Manquot;>
<subClassOf rdf:resource=quot;#Personquot;/>
<subClassOf rdf:resource=quot;#Malequot;/>
<label xml:lang=quot;enquot;>man</label>
<comment xml:lang=quot;enquot;>an adult male
person</comment>
</Class>
example
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a class declaration in RDFS
OWL
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<owl:Class rdf:ID=quot;Manquot;>
<owl:intersectionOf rdf:parseType=quot;Collectionquot;>
<owl:Class rdf:about=quot;#Malequot;/>
<owl:Class rdf:about=quot;#Personquot;/>
</owl:intersectionOf>
</owl:Class>
example
52 intersection of classes in OWL
specify meaning
with unique identifiers
< >…</ >
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link
to the world
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you are here
tens of billions
of triples already online, RDF is flying (e.g. http://sindice.com/ )
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Life
cycle
Design
Needs Evolution Diffusion
Manage
Evaluate Use
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diffusion identify, publish,
advertise, web, peer-to-peer and other networks,
standards (e.g., OWL)
Design
Needs Evolution Diffusion
Manage
Evaluate Use
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use in daily applications, in daily tasks
(find, monitor, combine, analyze, reuse, suggest
etc.), inferences, interfaces.
Design
Needs Evolution Diffusion
Manage
Evaluate Use
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evaluate c.f. needs + trace and
usage analysis, metrics from methods,
collective dimension and consensus
Design
Needs Evolution Diffusion
Manage
Evaluate Use
61
evolution alignment,
c.f. design + versioning, version
coherence checking and all dependencies
Design
Needs Evolution Diffusion
Manage
Evaluate Use
62
manage as any project,
complete methodologies
Design
Needs Evolution Diffusion
Manage
Evaluate Use
63
the domain trap
the application domain may be
different from the ontology domain
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I never saw a universal
ontology
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methods
e.g. rigidity in Onto Clean [Guarino & Welty]
Rigid φ+R φ is a necessary property for all its instances
Anti-Rigid φ~R φ is an optional property for all its instances
Constraint: φ~R can't subsume ψ+R
Person is ψ+R, Student is φ~R
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holistic
knowledge, but
finite ontologies
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building block
vs.
changing block
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ontology-based
doesn’t mean you need
an inference engine
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SSRSSLSSS
SSLSSLSSS
SSL
world-wide
errors Berry
inspired by Gérard
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acquisition & evolution
bottlenecks
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tagging
and other web 2.0 practices
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a tag
a data attached to an object
origins of geometry
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social tagging
collaboratively creating and
managing tags to annotate and
categorize content.
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folks onomy
the mass of users to organize the mass of data
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f olksonomy
folks~taxonomy, a subject indexing systems
created within internet communities. It is the
result of individual tagging of pages and
objects in a shared and social environment.
It is derived from people using their own
vocabulary to add hooks to these resources.
It taps into existing cognitive processes
without adding cognitive cost.
[Vander Wal, 2005] [Vander Wal, 2007][Rashmi Sinha, 2005]
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folksonomies
are not the opposite of
ontologies
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folksonomies
can be seen as a new
way to build and maintain
ontologies
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many tags
for many uses
cool
to compare with RR176
origins of geometry
send to Ted
絕對虛假
for the SysDev team
;-)
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many societies
my bookmarked page
socially shared bookmark
bookmark shared across
people an applications
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e.g. LOM (Learning Object Metadata)
has nine types of characteristics:
general, life-cycle, meta-metadata,
technical, educational, rights, relations,
annotation, classification
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scenario
S ?
knowledge transfer/(re)use/analysis?
evaluation/test/marking?
profiling/customizing?
feedback/curriculum management?
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Dublin core
Creative Commons
FOAF …
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take-home
summary and messages
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web”
“semantic
and not
“semantic web” [C. Welty, ISWC 2007]
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a lightweight ontology
allows us to do
lightweight reasoning
[J. Hendler, ISWC 2007]
90
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