Spezielle Kapitel aus Informatik:
Adaptive Hypermedia Systems

LVA - Name:
(Course name)

LVA - Nummer:
(Course number)

LVA - Typ:
(Course type)

Wochenstunden pro Sem.:
(Week-hours per Semester)

Vortragende(r):
(Lecturer)

Anmeldemodus:
(Registration)

Termine:
(Lecture dates)

Block (The dates and times of lectures will be decided once the course starts)
1st date:
15.10.2008, 17:15 - 18:00, T 911

Next date:
25.11.2008, 8:30 - 11:45, J 311 B

Inhalt der LVA:
(Course contents)

The course will cover a wide range of issues related to adaptive hypermedia, and will include a lot of examples from existing systems, as well as hands-on experience with an adaptation engine (which will also be used in the course's project). Below you can find an overview of the course topics, as well as a description of the course project.

During the course we will have a gues lecture of a leading figure in the field of Adaptive Hypermedia Systems, Prof. Dr. Paul M. E. De Bra of the Technical University of Eindhoven (TU/e). Prof. De Bra's group has developed the well-known AHA! open source adaptive hypermedia framework.

This course will be taught in parallel with an equivalent course taught by Prof. De Bra in the TU/e. This means that the teaching materials used in both courses will be the same, and the students of the two courses will have an opportunity to collaborate on the courses' joint project.

Course overview

• Introduction
  • We live in a “one size fits all” world!
  • Motivation for adaptivity in hypermedia
  • What can we adapt to?
  • What can be adapted and how?
  • Methods and techniques of adaptive hypermedia
  • Application areas
     
• User Modeling
  • What is being modeled?
    (knowledge, interests, goals and tasks, background, individual traits, context of work, etc.)
  • How is it being modeled?
    (feature-based vs. stereotype modeling, uncertainty-based user modeling)
  • Generic User Modeling Systems
    (requirements for GUM systems, and for sharing UM Data)
     
• Machine learning for adaptivity
  • In this section we will cover some basic machine learning methods that are typically used in adaptive hypermedia. We will also cover more recent approaches that are in wide use in commercial systems, such as collaborative filtering (what Amazon uses for personalized recommendations).
     
• Analysis of adaptation techniques
  • Adaptive navigation support
    (methods - what kinds of adaptation are useful; techniques - how can the adaptation be produced)
  • Adaptive content presentation
    (content - changing what is presented; presentation - changing how it is presented)
  • Simple adaptation mechanisms
     
• The AHAM reference architecture for adaptive hypermedia
  • Domain model
  • User model
  • Adaptation model
  • The AHAM rule language
     
• The AHA! adaptation engine
  • Overview of the AHA! framework and its capabilities, and of how adaptive web-based systems can be developed with it.
     
• Example Adaptive Hypermedia Systems
  • Personalized product recommendation
  • Personalized TV guide
  • Adaptive information management
  • Intelligent tutoring
  • Adaptive electronic textbooks
  • Adaptive tourist guides
  • etc.

Course project

The course project will involve the development of an adaptive web site using the AHA! system and its associatd authoring tools. The project will be carried out in groups, and people will have the opportunity to collaborate with fellow-students of the Technical University of Eindhoven, who will be attending the "parallel" course (see above for additional details).

The project is intended to let students gain hands-on experience with the course themes, and is mandatory. Additional information will be provided during the course.
 

LVA - Modus:
(Teaching notes)

Prüfung:
(Exams)

Literatur:
(Literature)

Sonstige Informationen:
(Additional information)

Weitere Auskünfte:
(Further inquiries)

Links zu anderen Semestern:
(Links to other semesters)