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Towards a Framework for
Open-Corpus Content Preparation
          supporting
 Adaptive Hypermedia Systems

         Killian Levacher
Outline

   Increasing importance of adaptive systems on the Web
   AHS impediments to full mainstream adoption
   Novel content preparation framework solution
   Framework benefits
   Novel challenges introduced
   Roadmap ahead
Consume
  Interact
    Author
Adaptive Systems are at Centre Stage of this
            Paradigm Shift
Content Availability Impedes AHS Full
            Mainstream Adoption

   Mainly due to low availability of suitable content in
terms of volume, style, diversity, meta-data, granularity…



 Manually Authored by Small groups of Users
 Lack of Diversity and Up to Date Content
 Pre-existing Documents
 Authored in particular Formats
Wealth of Information on the Web
 Content not directly re-usable by AHS
   • Usually built for single purpose usages
   •   Limited amount of meta-data
   •   Very heterogeneous (Style…)
   •   Different languages
   •   Very coarse grained
   • Contains noisy information
Adaptive Engine

 Content
Narration      User Model


   Adaptive System
Adaptive Engine

            Content

             Adaptive System



Narrative                               User Model
Adaptive Engine




Narrative                     User Model



             Content
Open Corpus Content Preparation
 Avail AHS with the wealth of open-corpus information
 Bridge the gap between open-corpus content & AHS specific
information requirements
 Fully decouple content from core adaptive system
 Service that prepares open-corpus content for AHS usage



 Automated  content preparation service
 Wide variety of up to date content
 Re-purposing of existing content
 No generic structure to comply with
Content Analysis Services




                     A Priori

 A Slice
   • is a semantically independent piece of content extracted
     from a pre-existing document
   • Is retrieved in a chosen format
   • represents a AH subjective perspective of a document
Content Analysis Services




          A Priori
                                   On Demand




                            AHA!   KnowledgeSea
Benefits of this Framework

 Open Corpus processing re-purposing content
 Automated content Slicing vs Manual Authorship
   • Possible solution to content authorship scalability
 Removal of content format dependency for AH
   • Content preparation approach solves Interoperability
     issues
 Pipelined approach enables new content annotators to
be plugged in seamlessly
 Concept of subjective slices of existing content
New Challenges Introduced
 Structural Segmenter fulfilling large domain and
processing speed requirements
 Semantic Annotator will be a critical component
   • How much semantic meta-data can we really aim
     for? Will it necessarily be domain dependant?
  • Has a direct influence on Slice Precision
Roadmap Ahead

 Selection or composition of a framework specific
structural segmenter
 Initial comparative evaluation of semantic analyzer to
evaluate the quality and volume of meta-data expected
 Implementation of framework within a Personalized
Multi-Lingual Customer Care System
Summary
 Content provision impedes the full mainstream adoption
of AHS
 Content provision should be fully loosely coupled with
adaptive systems
 Novel open-corpus preparation framework
 Solution provides content scalability, interoperability,
volume, diversity
 New challenges ahead
 Initial proof of concept planned within PMCC system
A Framework for Content Preparation to Support Open-Corpus Adaptive Hypermedia
Discussion
                        Ideas
         Questions
                  Comments

    Suggestions

More Related Content

A Framework for Content Preparation to Support Open-Corpus Adaptive Hypermedia

  • 1. Towards a Framework for Open-Corpus Content Preparation supporting Adaptive Hypermedia Systems Killian Levacher
  • 2. Outline  Increasing importance of adaptive systems on the Web  AHS impediments to full mainstream adoption  Novel content preparation framework solution  Framework benefits  Novel challenges introduced  Roadmap ahead
  • 4. Adaptive Systems are at Centre Stage of this Paradigm Shift
  • 5. Content Availability Impedes AHS Full Mainstream Adoption Mainly due to low availability of suitable content in terms of volume, style, diversity, meta-data, granularity…  Manually Authored by Small groups of Users  Lack of Diversity and Up to Date Content  Pre-existing Documents  Authored in particular Formats
  • 6. Wealth of Information on the Web  Content not directly re-usable by AHS • Usually built for single purpose usages • Limited amount of meta-data • Very heterogeneous (Style…) • Different languages • Very coarse grained • Contains noisy information
  • 7. Adaptive Engine Content Narration User Model Adaptive System
  • 8. Adaptive Engine Content Adaptive System Narrative User Model
  • 9. Adaptive Engine Narrative User Model Content
  • 10. Open Corpus Content Preparation  Avail AHS with the wealth of open-corpus information  Bridge the gap between open-corpus content & AHS specific information requirements  Fully decouple content from core adaptive system  Service that prepares open-corpus content for AHS usage  Automated content preparation service  Wide variety of up to date content  Re-purposing of existing content  No generic structure to comply with
  • 11. Content Analysis Services A Priori  A Slice • is a semantically independent piece of content extracted from a pre-existing document • Is retrieved in a chosen format • represents a AH subjective perspective of a document
  • 12. Content Analysis Services A Priori On Demand AHA! KnowledgeSea
  • 13. Benefits of this Framework  Open Corpus processing re-purposing content  Automated content Slicing vs Manual Authorship • Possible solution to content authorship scalability  Removal of content format dependency for AH • Content preparation approach solves Interoperability issues  Pipelined approach enables new content annotators to be plugged in seamlessly  Concept of subjective slices of existing content
  • 14. New Challenges Introduced  Structural Segmenter fulfilling large domain and processing speed requirements  Semantic Annotator will be a critical component • How much semantic meta-data can we really aim for? Will it necessarily be domain dependant? • Has a direct influence on Slice Precision
  • 15. Roadmap Ahead  Selection or composition of a framework specific structural segmenter  Initial comparative evaluation of semantic analyzer to evaluate the quality and volume of meta-data expected  Implementation of framework within a Personalized Multi-Lingual Customer Care System
  • 16. Summary  Content provision impedes the full mainstream adoption of AHS  Content provision should be fully loosely coupled with adaptive systems  Novel open-corpus preparation framework  Solution provides content scalability, interoperability, volume, diversity  New challenges ahead  Initial proof of concept planned within PMCC system
  • 18. Discussion Ideas Questions Comments Suggestions