1212 / Department of Computer Science Adaptive Hypermedia 2ID20 Prof. dr. Paul De Bra

Department of Computer Science

Adaptive Hypermedia2ID20

Prof. dr. Paul De Bra


Example Adaptive Hypermedia Systems• We show examples that are very different:

– AIMS: Adaptive Information Management System (TU/e+UT)

– ISIS-Tutor: Tutorial for Library Information System (Moscow State University and Univ. of Trier)

– SQL-Tutor: Intelligent Tutoring System for SQL (Canterbury, New Zealand)

– Interbook: Adaptive Electronic Textbooks (Univ. of Pittsburgh)

– INTRIGUE: adaptable tourist guide (Univ. of Torino)– TV Scout: personalized TV guide (GMD Darmstadt)– HERA: Data Integration and Presentation Generation in

Web-Based Information Systems (TU/e)– The ARIA Photo Agent (MIT) with commonsense reasoning


AIMS: Task-Based Information Retrieval• Agent-based Information Management System:

– concept visualization (using “aquabrowser”)– task-based search (keyword search extended with

task information)– user model: keeps track of user’s knowledge and

performed tasks– graphical user-interfaces for creating concepts,

tasks, courses, etc.– evaluated with students from Universiteit Twente


AIMS Global Information Model• Domain model: defines subject domain by

means of a concept map– concepts are linked to each other (“ontology”)

• Library model: defines relationship between documents and concepts– how relevant is a document for a given concept

• Course model: course topics and tasks– tasks are described using concepts, task description,

prerequisites, task status• Learner model: what the user has learned:

– course tasks, domain concepts, library documents– overlay model– built jointly by the user and the system


AIMS Student Interface


AIMS Instructor Domain Environment


AIMS Instructor Library Environment


AIMS Instructor Course Environment


AIMS Admin Environment


ISIS-Tutor: adaptive annotation/hiding• Tutor for CDS/ISIS library system

– CDS/ISIS is a library system for PCs sponsored by UNESCO– ISIS Tutor developed by Peter Brusilovsky and Leonid Pesin– descendent from an older system ITEM/P (Moscow State Univ.)– domain- and student model for monitoring student knowledge– tutor component to perform adaptive task sequencing– hypertext component lets students navigate through course

material.– learning environment lets users interact with ISIS– versions with adaptive link annotation and link removal– evaluated to determine learning effect of using adaptation– http://www.cs.joensuu.fi/~mtuki/www_clce.270296/Brusilov.html


ISIS Tutor with Link Annotation


ISIS Tutor with Link Removal+Annotation


Evaluation of ISIS Tutor (number of steps)

30

40

50

60

70

80

90

100

110

120

130

Un

its

Steps

Hiding

Annotation

Nonadaptive


Evaluation of ISIS Tutor (repetitions)

0

2

4

6

8

10

12

14

16

18

Ce

ll M

ea

n

Concept repetitions Unforced repetitions

Hiding

Annotation

Nonadaptive


Relationship between well-known AHS

ISIS-Tutor, MSU (1992-1994) ITEM/PG, MSU (1991-1993)

SQL-Tutor, MSU (1995-1998) ELM-ART, Trier (1994-1997)

InterBook, CMU (1996-1998) ELM-ART II, Trier (1997-1998)

ITEM/IP, MSU (1986-1994)


SQL Tutor• Knowledge-based tutor for the SQL language

– based on constraint-based modeling– currently deals only with the SELECT statement– users register with an initial knowledge level– system suggests problems based on the knowledge

level (based on which clause select, from, where, group by, having or order by the user needs to practice

– system was evaluated to find out whether it was useful and pleasant to use

– SQL-Tutor is described (and sometimes accessible) at: http://www.cosc.canterbury.ac.nz/~tanja/sql-tut.html


SQL Tutor, Main Window


Interbook• tool for adaptive electronic textbooks:

– authoring through Microsoft Word (+conversion tools)– domain model: concepts and prerequisite relationships– user model: overlay model, updated through “outcome

concepts” of read pages– adaptive link annotation– several additional tools: index, glossary, “teach me”– a good description of Interbook:

http://www7.scu.edu.au/programme/fullpapers/1893/com1893.htm

– Interbook (development) can be tried at the following address:

http://136.142.116.98/inter/Welcome.html


Interbook: textbook window


Interbook: Glossary and Concepts


Authoring for Interbook


Interbook: Evaluation• Goal: to find a value of adaptive annotation

– Electronic textbook about ClarisWorks– 25 undergraduate teacher education students– 2 groups: with/without adaptive annotation– Format: exploring + testing knowledge– Full action protocol

• Results:– Sequential navigation dominates (“continue” button)– Adaptive link annotation encourages non-sequential

navigation– Most students follow the “green” links


Intrigue: adaptive tourist guide • Allows for the planning of a trip

– stereotype user modeling– allows to plan a trip for a diverse group, for instance

parents with children– takes physical disabilities into account, age,

interests, etc.– can produce output in html or wml (for mobile

phone)– can be tried at:

http://silk.di.unito.it:8083/ishtar/intrigue.html


Intrigue: recommendation for 2 groups


Intrigue: combined recommendation


TV Scout: Personalized TV Guide• A cooperation between GMD-IPSI and

– Goal: Help users in creating their personal TV schedule

– Short-lived data (not a static database)– Low user effort required to “tune” the system– Filtering based on time and genre, information

provided by the stations– Users plan only for one day– TV Scout has a simple and an advanced interface,

with possibilities for collaborative filtering.


TV Scout: What’s on Tonight?


TV Scout: Setting Preferences• Preferred genres can

be indicated• Deeper genres are

more specific• Less general than

Boolean combinations


TV Scout: Forms and Graphical Interface


TV Scout: Evaluation / Feedback• Orientation is easy, but undo is missing• For some users the system is still too complex

(opening folders, buttons to small for visually impaired users)

• People liked the „grocery list“ (forms interface)• Overall it is useful and easy to use• High fun-factor!• Biggest success indicator is repeat visits by

users


HERA: Presentation Generation in WIS• Automatic generation of hypermedia interface

for data from integrated sources– adaptation to user preferences– adaptation to platform capabilities (devices)– generation of a whole website based on these

preferences– integration of heterogeneous data sources:

adaptation for the “deep Web”– A demo version is available (but not publicly because

of copyright issues on the data).


Hera Design Methodology

Hera Suite

Design Methodology

RequirementsAnalysis

ConceptualDesign

IntegrationDesign

ApplicationDesign

AdaptationDesign

PresentationDesign

(Search)Agent

inforequest

(meta) data

ConceptualModel Application

Model

info request(slice)

presentation

End User

RQL / RDF XSLT / XML

UserModel

PresentationModel

PresentationEngine

ApplicationEngine

IntegrationEngine

CuypersEngine

AdaptationEngine

info request HTML/WML

IntegrationModel

Semantic Layer Application Layer Presentation Layer


Hera: Conceptual Model Example


Hera: Application Model Example


Hera: Adaptation Model Example


Hera: Presentation Model Example

Bookcase regions

Screen rendering

bookcase

shelf

P.picture

painting

P.picture

P.name

…

Region

Attribute

(Associated to a certain painting P)

xy

right

below

Navigational Relationship

Spatial Relationship

0

1

2 0

P1 P2 P3

P4 P5 P6

P7

P1

‘Stone Bridge’ 1638 …

…

Priority (Priority 0 is always fulfilled)


Hera: Presentation Example


The ARIA Photo Agent (video)• Adaptive Linking between Text and Photos

– Text is used for searching as it is typed– Text is matched with photo descriptions

• keywords, people, place and time– Database with “common sense” used– Adaptive sorting (of photos = search results)– Automatic annotation of selected photos– Annotation (conceptual descriptions) of photos

can be manually updated– Project webpage:

http://web.media.mit.edu/~lieber/Lieberary/Aria/Aria-Intro.html


ARIA Screenshot

Documents

1212 / Department of Computer Science Adaptive Hypermedia 2ID20 Prof. dr. Paul De Bra