adaptive authoring of adaptive hypermedia

Adaptive Authoring of Adaptive Hypermedia

Maurice HendrixEindhoven University of

Technology & L3S Research Center

Hannover

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

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

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

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

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)

MOT hierarchy structure•Concept maps and lessons are conceptual

hierarchies

•We can represent them as tree structures

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

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>

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)

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

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

Theoretical Aspects: Formula

Where k(x) : the bag of keywords in x a : the publication in Sesame c : the concept in MOTWith an extended notion of intersection

card(k(a))

k(a))card(k(c)=c)rank(a,

Theoretical Aspects: Extended AlgorithmIF (card(k(n1) ∩ k(a)) = card(k(n2) ∩ k(a)))

THENIF (card(k(n2) > card(k(n1)) THEN connect

to n1ELSEIF (card(k(n2) < card(k(n1)) THEN

connect to n2ELSEIF (card(k(n1) = card(k(n2)) THEN

IF (n1 higherthan n2) THEN connect to n1

ELSE connect to n2ELSEIF (card(k(n1) ∩ k(a)) > card(k (n2) ∩ k(a))) THEN connect to n1ELSEIF (card(k(n1) ∩ k(a)) < card(k(n2) ∩ k(a))) THEN connect to n2

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

Demo

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

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