mazette: multi-agents musette for sharing and reusing ontologies jesus arana, salima hassas and...
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MAZETTE: Multi-agents MAZETTE: Multi-agents MUSETTE for sharing and MUSETTE for sharing and
reusing ontologiesreusing ontologies
Jesus Arana, Salima Hassas and Yannick Prié
28 October 200428 October 2004
Claude Bernard University, Lyon 1
Lyon Research Center for Images and Intelligent information Systems
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MotivationMotivation
To modelise the persons that work in the creation of learning distance courses in order to create an application to assist them taking into account the users’ experience.
To modelise how they work, in order to create assistances based in their traces to reuse the way they work, creating common sources of knowledge (ontology co-construction) in a emergent way.
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PlanPlan
Motivation The context : documentary spaces, collective
tasks, ontologies and documents. Modelling and using experience through
MUSETTE. MAZETTE Use scenarios Our application and its domain Conclusion, future works
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Context of studyContext of study
Documentary space, – Documents, annotations and personal and
collective ontologies
Collective task– Sharing a documentary space to realize a
computer-mediated task.
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OntologiesProvide the common vocabulary of a specific domain defining terms meaning and relations. [Gomez-Perez, 1999]
Document Numeric documents, files and that are part of the user’s
documentary space.
… … Context of studyContext of study
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MUSETTE MUSETTE ApproachApproach
« Modeling the USEs and Tasks for Tracing Experience »
MUSETTE
USER-SYSTEMINTERACTION
OBSERVATION& EXTRACT OF USER TRACES
EXTRACTION OF SIGNIFICANT EPISODES
USERASSISTANCE
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Observer Agent
Observer Agent
Use ModelUse Model
Observation
Trace Generation
User
Interaction
ObservedSystem
ObservedSystem
AssistantAgents
Episodes Reuse
Observation ModelObservation Model
Episodes Extraction
Generic Trace AnalyserGeneric Trace Analyser
Task Signature 1
Task Signature 1
TaskSignature 2
TaskSignature 2
EpisodesEpisodes EpisodesEpisodes
Primitive TracePrimitive Trace
EpisodesExtractionTask
Signature 1
Task Signature 1
Task Signature 2
Task Signature 2
EpisodesEpisodes EpisodesEpisodes
Generic Trace AnalyserGeneric Trace Analyser
AssistantAgents
AssistantAgents
Episodes Reuse
MUSETTE Approach.MUSETTE Approach.
ObserverAgent
ObserverAgent
Observation
Trace Generation
Observation ModelObservation Model
Use ModelUse Model
Primitive TracePrimitive Trace
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Observable
Object of interest Observation
EventRelations Entity
State 5
State
State 6 State 7Transition 5 Transition 6
Transition
Link1
Fr
Link2Page 1
Page 2
FrPersistence
Click1
Lang1
Bm1En
Page 2
Use model
ImageLink
Cust
Image
Page
Lang
Sav
Bm
Click
Co
ns
tra
ints
Use Model and a simple traceUse Model and a simple trace
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Explained Task SignaturesExplained Task Signatures Examples (EXTASI’S) Examples (EXTASI’S)
Task Signature : Bookmarking un interesting site
Page link Click Page bm
Inner Page
CoveringPage
Same site
Allows to retrieve the innerpage
Task Signature : Changing the language
Page Page
Trait Traitlang
Thispage is prefered in this language
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DomainDomain
Apply model -> Create application
Modelise the persons that create learning distance courses in order to conceive an application to assist users the creation of the courses.
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Mazette ApproachMazette Approach
Mazette= Multi-Agents MUSETTE
Mazette vs Musette
ObjectiveObjectiveTo provide assistance based on the sharing and reuse of users’ experience, facilitating the co-construction of ontologies, by articulating them or unify them.
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Mazette ApproachMazette Approach
Use Model
QueryTrace generation
EXTASI
Storing
User 1
Documentary space
ALTER EGOALTER EGO
Use ModelUse Model
Trace generation
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Query
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