Context sensitivity for networked ontologies Igor Mozetič, Marko Grobelnik, Damjan Bojadžijev...
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![Page 1: Context sensitivity for networked ontologies Igor Mozetič, Marko Grobelnik, Damjan Bojadžijev Jozef Stefan Institute Slovenia.](https://reader035.fdocuments.us/reader035/viewer/2022062412/5a4d1b097f8b9ab05998998b/html5/thumbnails/1.jpg)
Context sensitivity for networked ontologies
Igor Mozetič, Marko Grobelnik, Damjan BojadžijevJozef Stefan InstituteSlovenia
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NeOn, Rome, 21 Mar 2006
JSI 2
text context
explicit implicit
global local
text
I’m here who, where
text expl(context)
text_1context_1
+
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NeOn, Rome, 21 Mar 2006
JSI 3
Overview
Formalizing context Cyc Semantic Web C-OWL Probabilistic approaches JSI related work
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NeOn, Rome, 21 Mar 2006
JSI 4
McCarthy [1993]
AI: modelling of context and use in automated reasoning
implicit -> explicit ist( context, proposition ) context = collection of assumptions
(generalization of, partially known) entering and exiting,
nesting, lifting, transcending, …
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NeOn, Rome, 21 Mar 2006
JSI 5
Cyc [Lenat, Guha]
Cyc KB = set of microtheories (Mt) Microtheory = set of axioms
shared assumptions, topic internally consistent localized (more efficient) reasoning preconditions = context in which Mt is applicable
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NeOn, Rome, 21 Mar 2006
JSI 6
Cyc (example)
ist( NaiveStateChangeMt, isa( ?X, Freezing ) & outputsCreated( ?X, ?Obj ) => stateOfMatter( ?Obj, SolidStateMatter ))
NaiveStateChangeMt domainAssumptions: forAll ?U isa( ?U, StateOfMatterChangeEvent ) => isa( ?U, CreationOrDestructionEvent )
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NeOn, Rome, 21 Mar 2006
JSI 7
Context for Semantic Web [Guha et al]
AI SWscope, complexity of phenomena
scale (comp. complexity),distributed sources,ease of use
Aggregation from different sources. Issues:• class differences• property type differences• point of view• implicit time• approximations
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NeOn, Rome, 21 Mar 2006
JSI 8
C-OWL [Giunchiglia et al]:Contextualizing ontologies
Ontologies Contexts
Global, shared modelEncode common viewCombining by import
Global semantics
Local modelsEncode each party’s viewCombining by explicit mappingsLocal Models Semantics
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NeOn, Rome, 21 Mar 2006
JSI 9
OWL: Global semantics for multiple (networked) ontologies
sharedmodel
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NeOn, Rome, 21 Mar 2006
JSI 10
OWL: Global semantics for multiple (networked) ontologies
sharedmodel
import
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NeOn, Rome, 21 Mar 2006
JSI 11
C-OWL: Local model semantics
local models
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NeOn, Rome, 21 Mar 2006
JSI 12
C-OWL: Mappings
contextualizedontology
context
context
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NeOn, Rome, 21 Mar 2006
JSI 13
C-OWL ontology is a pair:
OWL ontology (target): concepts individuals roles
mappings (bridge rules): equivalence onto into compatible incompatible
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NeOn, Rome, 21 Mar 2006
JSI 14
C-OWL example
OWL ontology (target) + mappings (bridge rules)
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NeOn, Rome, 21 Mar 2006
JSI 15
C-OWL of any use?
Import ontology vs. define context mappings? (diversity as defect vs. feature)
Semantic Web = Web of Semantic links ? (context mappings)
Discovering context mappings = core issue in building Semantic Web ?
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NeOn, Rome, 21 Mar 2006
JSI 16
JSI related work
Parametric temporal ontology Simultaneous ontologies User profiling Implicit document context (links)
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NeOn, Rome, 21 Mar 2006
JSI 17
Temporal ontology
Temporal algebra [Allen]: event = temporal interval relations: before, meets, starts, finishes, …
week(now)
day(sun)day(mon) meets meets
starts finishes
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NeOn, Rome, 21 Mar 2006
JSI 18
Temporal ontology
Temporal algebra [Allen]: event = temporal interval relations: before, meets, starts, finishes, …
week(now) week(now+1)
day(sun)day(mon) meets meets
starts finishes
meets
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NeOn, Rome, 21 Mar 2006
JSI 19
Temporal ontology
Temporal algebra [Allen]: event = temporal interval relations: before, meets, starts, finishes, …
week(now) week(now+1)
day(sun)day(mon) meets meets
starts finishes
day(now)day(now-1) meets
meets
day(now+1)meets
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NeOn, Rome, 21 Mar 2006
JSI 20
Temporal reasoning
Temporal algebra [Allen]: event = temporal interval relations: before, meets, starts, finishes, …
week(now) week(now+1)
day(sun)day(mon) meets meets
starts finishes
day(now)day(now-1) meets
meets
equals
day(now+1)meets
?
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NeOn, Rome, 21 Mar 2006
JSI 21
Temporal reasoning
Temporal algebra [Allen]: event = temporal interval relations: before, meets, starts, finishes, …
week(now) week(now+1)
day(sun)day(mon) meets meets
starts finishes
day(now)day(now-1) meets
meets
equals
day(now+1)meets
day(mon)
starts
![Page 22: Context sensitivity for networked ontologies Igor Mozetič, Marko Grobelnik, Damjan Bojadžijev Jozef Stefan Institute Slovenia.](https://reader035.fdocuments.us/reader035/viewer/2022062412/5a4d1b097f8b9ab05998998b/html5/thumbnails/22.jpg)
NeOn, Rome, 21 Mar 2006
JSI 22
Temporal reasoning
Temporal algebra [Allen]: event = temporal interval relations: before, meets, starts, finishes, …
week(now) week(now+1)
day(sun)day(mon) meets meets
starts finishes
day(now)day(now-1) meets
meets
equals
day(now+1)meets
meets day(mon)
starts
![Page 23: Context sensitivity for networked ontologies Igor Mozetič, Marko Grobelnik, Damjan Bojadžijev Jozef Stefan Institute Slovenia.](https://reader035.fdocuments.us/reader035/viewer/2022062412/5a4d1b097f8b9ab05998998b/html5/thumbnails/23.jpg)
NeOn, Rome, 21 Mar 2006
JSI 23
Temporal reasoning
Temporal algebra [Allen]: event = temporal interval relations: before, meets, starts, finishes, …
week(now) week(now+1)
day(sun)day(mon) meets meets
starts finishes
day(now)day(now-1) meets
meets
equals
day(now+1)meets
meets day(mon)
starts
equals
![Page 24: Context sensitivity for networked ontologies Igor Mozetič, Marko Grobelnik, Damjan Bojadžijev Jozef Stefan Institute Slovenia.](https://reader035.fdocuments.us/reader035/viewer/2022062412/5a4d1b097f8b9ab05998998b/html5/thumbnails/24.jpg)
NeOn, Rome, 21 Mar 2006
JSI 24
Parameterized temporal ontology Parameters:
now order of magnitude past - future
now-1 now now+1 now+2
day
wee
k m
onth
ye
ar
deca
de
now = ?
context
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NeOn, Rome, 21 Mar 2006
JSI 25
News analysis
earthquake tsunami tsunami tsunami tsunami
News stream:
the same? yet another one?
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NeOn, Rome, 21 Mar 2006
JSI 26
A temporal model: Tsunami
Earthquake
Tsunami
Search & Rescue Rebuilding
~minutes
~hours
~days ~months
E T S&R
25.dec 26.dec 27.dec 28.dec 29.dec 30.dec 31.dec 1.jan 2.jan 3.jan
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NeOn, Rome, 21 Mar 2006
JSI 27
News analysis: Temporal model = Context
earthquake tsunami tsunami tsunami tsunami
News stream:
model of tsunami
provides contextfor subsequentevents
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NeOn, Rome, 21 Mar 2006
JSI 28
Summary
Parameterized ontology Context determines parameters
when? how long? order of magnitude
Temporal model selected by events provides context