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Adaptive Authoring of Adaptive Hypermedia

Maurice Hendrix Eindhoven University of Technology & L3S Research Center Hannover. Adaptive Authoring of Adaptive Hypermedia. Outline. Goal and Motivation Problem description Initial Environment Theoretical Aspects of Development Implementation Demo

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Adaptive Authoring of Adaptive Hypermedia

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  1. Maurice Hendrix Eindhoven University of Technology & L3S Research Center Hannover Adaptive Authoring of Adaptive Hypermedia

  2. Outline • Goal and Motivation • Problem description • Initial Environment • Theoretical Aspects of Development • Implementation • Demo • Conclusions: Solutions, Problems & further work

  3. Goal and Motivation • We want to make the authoring task easier • Manual annotation is the bottleneck of authoring of adaptive hypermedia • We want to do this by integrating an authoring environment into a semantic desktop environment

  4. Problem description & plan • We want to make the authoring task of adaptive hypermedia easier by integrating and authoring system and a semantic desktop environment • Find out how to achieve this integration and how to (semi-)automatically populate GM & DM • Extend MOT with the necessary functionality

  5. Initial Environment (MOT) • My Online Teacher (MOT) authoring environment for adaptive hypermedia • Beagle++ semantic desktop environment

  6. My Online Teacher (MOT) • WWW authoring of adaptive hypermedia system using 5 layer model, most important for us are DM (containing concepts) and GM (containing lessons) • Domain model (DM) • Goal and constraints model (GM) • Adaptation model (AM) • User models (UM) • Presentation model (PM)

  7. MOT hierarchy structure • Concept maps and lessons are conceptual hierarchies • We can represent them as tree structures

  8. MOT: CAF • Mot uses portable CAF XML format CAF format is commonly used among other Adaptive Hypermedia systems • CAF describes the lesson in the goal model and the uses conceptmaps in the domain model

  9. MOT: CAF example • <domainmodel><concept><name>test</name> • <concept><name>tree</name> • <attribute><name>title</name> • <contents>tree</contents> • </attribute> • </concept> • </concept> • </domainmodel> • <goalmodel><lesson weight="0" label=""> • <link weight="0" label="">test\tree\title</link> • </lesson></goalmodel>

  10. Beagle++ • Extended Beagle desktop search tool • Generates and stores meta-data concerning files, emails, publications, bookmarks • Uses a Lucene full-text index and a Sesame RDF store for the meta data • Both indices are updated upon events (like file creation, file adaptation)

  11. Beagle++: meta-data • REF metadata describing resources like articles with attributes like conference, stored_as • Example:

  12. Theoretical Aspects: Enriching • The enricher application queries the Sesame database store via seRql queries which look like this: • SELECT Title • FROM { bplus:Publication} art:title {bplus:Title} • WHERE bplus:Publication = bplus:Attachment • The results are given a ranking by using one of the following methods and are added to the concept with the highest ranking

  13. Theoretical Aspects: Formula • Where k(x) : the bag of keywords in x • a : the publication in Sesame • c : the concept in MOT • With an extended notion of intersection

  14. Theoretical Aspects: Extended Algorithm • IF (card(k(n1) ∩ k(a)) = card(k(n2) ∩ k(a))) THEN • IF (card(k(n2) > card(k(n1)) THEN connect to n1 • ELSEIF (card(k(n2) < card(k(n1)) THEN connect to n2 • ELSEIF (card(k(n1) = card(k(n2)) THEN • IF (n1 higherthan n2) THEN connect to n1 • ELSE connect to n2 • ELSEIF (card(k(n1) ∩ k(a)) > card(k (n2) ∩ k(a))) THEN connect to n1 • ELSEIF (card(k(n1) ∩ k(a)) < card(k(n2) ∩ k(a))) THEN connect to n2

  15. Implementation • Import / export of CAF XML format in PHP • Export of lessons in RDF format by XSLT transformation of CAF • Java application which parses CAF XML format, searches Sesame RDF store and adds articles to the lesson

  16. Demo

  17. Conclusions: work performed • The task of manual authoring of adaptive hypermedia has been made easier by the integration of the authoring environment with the semantic desktop environment • By the application of some techniques for malleable schemas evolving environments have been made possible to some degree

  18. Conclusions: further work • Obtaining full flexibility towards evolving schemas • Automatic generation of adaptation rules and more advanced labelling and weighting • More general integration of authoring systems with semantic desktop environments

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