Diapositive 1

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Transcript Diapositive 1

OPALES Demonstration
Antoine Isaac
CWI – Feb. 22nd 2006
OPALES
 French Project (RIAM, 2001-2003)
 Partners:
• « Developers »
• INA (Coordinator)
• LIRMM (IHM, GC)
• CS
• « Users »
• CNRS (video library)
• MSH (humanities, communication)
• CNDP (educational material)
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« Tools to share knowledge in
educational/scientific communities »
 Goals
• Sharing and exploiting AV resources
• Fitting the needs of various specific user communities
 Approach
• Accessing document via annotations
• Similar to classical indexing approach
Interpretation of AV content used for exploitation
• Ensuring the relevance of annotation for communities
and applications
• Using points of view
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Points of view
 Exploitation of annotation/indexes needs semantic
continuity
• Shared interpretation/coherent manipulation for
indexer/searcher/system
 OPALES points of view
• Mirror specific application/community needs
• Embody annotation policies
• Gather users who choose them for creating or filtering annotations
 Thorough experiments with 2 points of view
• Ethnology-oriented analysis of videos regarding childhood
• Educational exploitation of geographic information films
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Points of view and annotation/search
policies
 Free-text annotation and search
• Natural interpretation of AV content
 Form-based annotation and search
• Predefined structure
• Basic control (value lists)
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OPALES Forms
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Points of view and annotation/search
policies
 Free-text annotation and search
• Natural interpretation of AV content
 Form-based annotation and search
• Predefined structure
• Basic control (value lists)
 Ontology-based annotation and search
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Ontology-based annotation and search
 Explicit and flexible structuring of index elements
• Added value of relations for rich indexing
Conceptual Graphs formalism
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Ontology-based annotation
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Ontology-based annotation and search
 Explicit and flexible structuring of index elements
 Control ensured by formal specifications
 Inference
• Taking into account (viewpoint-specific) implicit
knowledge to link queries to indexes
Cogitant CG inference engine
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Problems of ontology-based approach
 Complex indexing process
• Difficult to get accustomed to
• Especially for people not used to KR
 Coupling design of complex ontological
knowledge with use
• Legitimate conceptualisation w.r.t. application and
practice
• Specification of formal inference knowledge
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DOE ontology editor
 Semi-informal semantics [Bachimont]
• Differential principles inter-defining notions by
similarities and differences
• Meaning naturally linked to an application domain
• Compatible with extraction of ontology elements from
textual resources
[Véronique Malaisé]
• Compatible with further formalization
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DOE
http://opales.ina.fr/public [Bachimont, Isaac, Troncy]
(now http://homepages.cwi.nl/~troncy/DOE/ !)
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Indexing patterns
 Determine relational template recurrent in aimed
information practices
• Dependent on point of view
 Propose those structures to the indexer as a
starting point for description
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Indexing patterns: example (1)
English
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Indexing patterns: example (3)
English
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Patterns and reasoning
 Comparison index/query
Pattern as an implicit pivotal structure, compensating for
description/query variations
 Inferring facts from pattern structure
Entity
hasParticipant
Action
isLocatedAt
Object/Place
isLocatedAt
 Inferring pattern-fitting facts from different structure
Entity
hasParticipant
Action
isLocatedAt
Place
isLocatedAt
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Conclusion
 Points of view as materialization of indexing and
exploitation strategies
 Knowledge-based tools
• Expressivity, control and inference
 Experimentation (two qualitative evaluations with
domain users) shows that there are obstacles:
• No familiarity of targeted users with formal techniques
• Difficulty for the knowledge workers to design proper
ontological resources for each point of view
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Conclusion
 Experimentation shows that approach is made feasible by:
• Ontologies linked in quite a natural way to meanings and practices
targeted by points of views
• Differential principles help ontology designer’s work and final users’
understanding
• Formalizing users needs by Indexing Patterns
• Both for description and query
• Also legitimates ontology designers’ work
• Turning to “relational” reasoning for compensating variations
[Remark: complexity goes now for KR engine]
Techniques to ensuring semantic continuity in ontologybased indexing and search
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THANK YOU !
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Back
Childcare use pattern
Posture
hasInstrument
Tool
isLocatedAt
OpeningDefined
Place
hasPosture
Mother
hasAgent
Child
hasPatient
HygienicCare
isMotherOf
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hasLocation
Feature
FunctionDefined
Place
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Back
Specialised index
Standing
hasInstrument
Bawl
hasPosture
hasAgent
Drying
Mother
hasAgent
Bathing
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Child
ExteriorLocation
hasLocation
Feature
isMotherOf
hasPatient
isLocatedAt
hasPatient
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IndividualHouse
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