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From Adaptive Hypermedia to
the Adaptive Web
… and beyond
Peter Brusilovsky
School of Information Sciences
University of P...
WWW: One Size Fits All?
• Unknown before variety of users
• Yet almost all of them offer the same content and
the same lin...
What can be taken into
account?
• Knowledge about the content and the
system
• Short-term and long-term goals
• Interests
...
User Model
Collects information
about individual user
Provides
adaptation effect
Adaptive
System
User Modeling side
Adapta...
Outline
• How hypertext and hypermedia can become
adaptive?
• What constitutes the Adaptive Web?
• What we have learned fr...
From AH to AW and Beyond
UM/NLG ITSHT
1G AH
2G AH
3G AH
IR/IFSearch, User Diversity
Social Navigation
Classic Adaptive
Hyp...
Classic Adaptive Hypermedia
UM ITSHT
1G AH
2G AH
3G AH
IR/IFSearch, User Diversity
Social Navigation
Classic Adaptive
Hype...
Do we need Adaptive
Hypermedia?
Hypermedia systems are almost adaptive but ...
Different people are different
Individual...
So, where we may need AH?
• Educational Hypermedia
– Hypadapter, Anatom-Tutor, ISIS-Tutor,
Manuel Excell, ELM-ART, InterBo...
What Can Be Adapted?
• Web-based systems = Pages + Links
• Adaptive presentation
– content adaptation
• Adaptive navigatio...
Adaptive Presentation: Goals
• Provide the different content for users with
different knowledge, goals, background
• Provi...
Adaptive presentation
techniques
• Conditional text filtering
– ITEM/IP
• Adaptive stretchtext
– MetaDoc, KN-AHS
• Frame-b...
Conditional text filtering
If switch is known and
user_motivation is high
Fragment 2
Fragment K
Fragment 1
• Similar to UN...
Adaptive Stretchtext (PUSH)
Adaptive presentation:
evaluation
• MetaDoc: On-line documentation system,
adapting to user knowledge on the subject
• Rea...
Adaptive navigation support:
goals
• Guidance: Where I can go?
– Local guidance (“next best”)
– Global guidance (“ultimate...
Adaptive navigation support
• Direct guidance
• Hiding, restricting, disabling
• Generation
• Sorting
• Annotation
• Map a...
Adaptive annotation: Icons
Annotations for topic states in Manuel Excell: not seen (white lens) ;
partially seen (grey len...
Adaptive annotation: Font
color
Annotations for concept states in ISIS-Tutor: not ready (neutral); ready
and new (red); se...
Adaptive hiding
Hiding links to concepts in ISIS-Tutor: not ready (neutral) links are
removed. The rest of 64 links fits o...
Adaptive annotation and
removing
QuickTime™ and aTIFF (LZW) decompressorare needed to see this picture.
Evaluation of Adaptive Link
Sorting
• HYPERFLEX: IR System
– adaptation to user search goal
– adaptation to “personal cogn...
Evaluation of Adaptive Link
Annotation and Hiding
• ISIS-Tutor, an adaptive tutorial
• The students are able to achieve th...
THM1: It works!
• Adaptive presentation makes user to
understand the content faster and better
• Adaptive navigation suppo...
THM2: AH is best of both
worlds
• The Artificial Intelligent approach: machine
intelligence makes a decision for a human
–...
Adaptive Web
UM ITSHT
1G AH
2G AH
3G AH
IR/IFSearch, User Diversity
Social Navigation
Classic Adaptive
Hypermedia
Adaptive...
Adaptive Web: Why?
Different people are different
Individuals are different at different times
"Lost in hyperspace”
La...
Adaptive Hypermedia Goes
Web
• Implementation of classic technologies
in classic application areas on the new
platform (bu...
Adaptive
hypermedia
technologies
Adaptive
presentation
Adaptive
navigation support
Direct guidance
Adaptive link
sorting
A...
InterBook: Web-Based AH
• An authoring shell and a delivery
system for Web-based electronic
textbooks
• Explores several a...
Adaptive annotation in
InterBook
1. State of concepts (unknown, known, ..., learned)
2. State of current section (ready, n...
Bookshelves and books
Book view
Glossary view
Goal-based learning: “help” and “teach this”
Results
• No overall difference in performance
• Sequential navigation dominates
...but ...
• Adaptive annotation encourag...
THM3: AH is not a Silver
Bullet
• A viewpoint: AH is an alternative to user-
centered design. No need to study the user -
...
The Need to Find It
• Background
– Adaptive Information Retrieval and Filtering
– Machine Learning
• Old techniques
– Guid...
THM4: Not all adaptive Web
systems are adaptive
hypermedia
• Many IR and IF filtering systems use an old
search - oriented...
User Modeling Challenges
• Low bandwidth for user modeling
– Extended user feedback
• Rating, bookmarking, dowloading, pur...
Application Areas: Old and
New
• Web-based education
• InterBook, ELM-ART, AHA!, KBS-Hyperbook, MANIC
• On-line informatio...
Integrated Adaptive Web
Systems
• Integrate several “systems”,
traditionally independent, inside one
Web application
• Sev...
Exploring Integrated Systems
• ELM-ART (1996-1998) - integrated ITS for
LISP programming
• ADAPTS (1998-1999) - integrated...
Adaptive Information Services
• Early prototypes: Basaar, FAB, ELFI
• Integrates content-based and collaborative
technolog...
ELM-ART: Integrated Web-
based Adaptive Educational
System
• Model: adaptive electronic textbook
– hierarchical textbook
–...
Adaptivity in ELM-ART
• Adaptive navigation support
• Adaptive sequencing
• Adaptive testing
• Adaptive selection of relev...
ANS + Adaptive testing
Adaptive Diagnostics
Similarity-Based Navigation
Architecture for integration of:
– Diagnostics
– Technical Information
– Performance-oriented Training
 A demonstration ...
Video clips
(Training)
Schematics
Engineering
Data
Theory of
operation
Block
diagrams
Equipment
Simulations
(Training)
Equ...
UserModel
Diagnostics
Content
Navigation
What task to doSystem health
What content is
applicable to this
task and this use...
The
result
Maintenance
history
Preprocessed,
condition-based
inputs
Technician
and Operator
Observations
Sensor inputs
(e....
Integrated interface
THM5: Not all areas are ready
for the Adaptive Web
• An attempt to implement adaptive Web-based
education in Carnegie Tech...
Mobile Adaptive Web
UM ITSHT
1G AH
2G AH
3G AH
IR/IFSearch, User Diversity
Social Navigation
Classic Adaptive
Hypermedia
A...
The Need to Be Mobile
• Background
– Technology: wearables, mobiles, handhelds…
– GIS and GPS work
– HCI: Ubiquitous Compu...
New Application Areas
• Mobile handheld guides
– Museum guides: HYPERAUDIO, HIPS
– City guides: GUIDE
• Mobile recommender...
4th
Generation?
1G AH
2G AH
3G AH
IR/IFSearch, User Diversity
Social Navigation
Classic Adaptive
Hypermedia
Adaptive Web
M...
3D Web
• Web is not 2D anymore - it includes a good
amount of VR content
• 3D offers more power and supports some
unique w...
Adaptive 3D Web?
• Motivated by a pioneer work…
– Luca Chittaro and Roberto Ranon Adding adaptive features to
virtual real...
Adaptive Navigation Support
in 3D
• Joint work with Stephen Hughes, Michael
Lewis, Jeffrey Jacobson, SIS Usability Lab
• H...
More information...
• Adaptive Hypertext and Hypermedia Home Page:
http://wwwis.win.tue.nl/ah/
• Brusilovsky, P., Kobsa, A...
From adaptive hypermedia to the adaptive Web
From adaptive hypermedia to the adaptive Web
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From adaptive hypermedia to the adaptive Web

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Slides for invited talk: Brusilovsky, P. (2003) From adaptive hypermedia to the adaptive Web. In: J. Ziegler and G. Szwillus (eds.) Interaktion in Bewegung. (Proceedings of Mensch & Computer 2003, Stuttgart, September 7-10, 2003) Stuttgart, Germany: B. G. Teubner, pp. 21-2

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From adaptive hypermedia to the adaptive Web

  1. 1. From Adaptive Hypermedia to the Adaptive Web … and beyond Peter Brusilovsky School of Information Sciences University of Pittsburgh, USA peterb@mail.sis.pitt.edu http://www2.sis.pitt.edu/~peterb
  2. 2. WWW: One Size Fits All? • Unknown before variety of users • Yet almost all of them offer the same content and the same links to all – Stores – Museums – Courses – News sites • Adaptive Web-based systems and sites offer an alternative. They attempt to treat differently users that are different from the system’s point view
  3. 3. What can be taken into account? • Knowledge about the content and the system • Short-term and long-term goals • Interests • Navigation / action history • User category,background, profession, language, capabilities • Platform, bandwidth, context…
  4. 4. User Model Collects information about individual user Provides adaptation effect Adaptive System User Modeling side Adaptation side Adaptive systems Classic loop “user modeling - adaptation” in adaptive systems
  5. 5. Outline • How hypertext and hypermedia can become adaptive? • What constitutes the Adaptive Web? • What we have learned from our work on Adaptive Hypermedia and the Adaptive Web – Take Home Messages (look for THM!)
  6. 6. From AH to AW and Beyond UM/NLG ITSHT 1G AH 2G AH 3G AH IR/IFSearch, User Diversity Social Navigation Classic Adaptive Hypermedia Adaptive Web Mobile Adaptive Web UbiComp Context Modeling Affective Computing
  7. 7. Classic Adaptive Hypermedia UM ITSHT 1G AH 2G AH 3G AH IR/IFSearch, User Diversity Social Navigation Classic Adaptive Hypermedia Adaptive Web Mobile Adaptive Web UbiComp Context Modeling Affective Computing 1990-1996
  8. 8. Do we need Adaptive Hypermedia? Hypermedia systems are almost adaptive but ... Different people are different Individuals are different at different times "Lost in hyperspace” We may need to make hypermedia adaptive where .. There us a large variety of users Same user may need a different treatment The hyperspace is relatively large
  9. 9. So, where we may need AH? • Educational Hypermedia – Hypadapter, Anatom-Tutor, ISIS-Tutor, Manuel Excell, ELM-ART, InterBook, AHA • On-line Information systems – MetaDoc, KN-AHS, PUSH, HYPERFLEX • On-line Help Systems – EPIAIM, HyPLAN, LISP-Critic, ORIMUHS
  10. 10. What Can Be Adapted? • Web-based systems = Pages + Links • Adaptive presentation – content adaptation • Adaptive navigation support – link adaptation
  11. 11. Adaptive Presentation: Goals • Provide the different content for users with different knowledge, goals, background • Provide additional material for some categories of users – comparisons – extra explanations – details • Remove irrelevant piece of content • Sort fragments - most relevant first
  12. 12. Adaptive presentation techniques • Conditional text filtering – ITEM/IP • Adaptive stretchtext – MetaDoc, KN-AHS • Frame-based adaptation – Hypadapter, EPIAIM • Natural language generation – PEBA-II, ILEX
  13. 13. Conditional text filtering If switch is known and user_motivation is high Fragment 2 Fragment K Fragment 1 • Similar to UNIX cpp • Universal technology – Altering fragments – Extra explanation – Extra details – Comparisons • Low level technology – Text programming
  14. 14. Adaptive Stretchtext (PUSH)
  15. 15. Adaptive presentation: evaluation • MetaDoc: On-line documentation system, adapting to user knowledge on the subject • Reading comprehension time decreased • Understanding increased for novices • No effect for navigation time, number of nodes visited, number of operations
  16. 16. Adaptive navigation support: goals • Guidance: Where I can go? – Local guidance (“next best”) – Global guidance (“ultimate goal”) • Orientation: Where am I? – Local orientation support (local area) – Global orientation support (whole hyperspace)
  17. 17. Adaptive navigation support • Direct guidance • Hiding, restricting, disabling • Generation • Sorting • Annotation • Map adaptation
  18. 18. Adaptive annotation: Icons Annotations for topic states in Manuel Excell: not seen (white lens) ; partially seen (grey lens) ; and completed (black lens)
  19. 19. Adaptive annotation: Font color Annotations for concept states in ISIS-Tutor: not ready (neutral); ready and new (red); seen (green); and learned (green+)
  20. 20. Adaptive hiding Hiding links to concepts in ISIS-Tutor: not ready (neutral) links are removed. The rest of 64 links fits one screen.
  21. 21. Adaptive annotation and removing QuickTime™ and aTIFF (LZW) decompressorare needed to see this picture.
  22. 22. Evaluation of Adaptive Link Sorting • HYPERFLEX: IR System – adaptation to user search goal – adaptation to “personal cognitive map” • Number of visited nodes decreased (significant) • Correctness increased (not significant) • Goal adaptation is more effective • No significant difference for time/topic
  23. 23. Evaluation of Adaptive Link Annotation and Hiding • ISIS-Tutor, an adaptive tutorial • The students are able to achieve the same educational goal almost twice as faster • The number of node visits (navigation overhead) decreased twice • The number of attempts per problem to be solved decreased almost 4 times (from 7.7 to 1.4-1.8)
  24. 24. THM1: It works! • Adaptive presentation makes user to understand the content faster and better • Adaptive navigation support reduces navigation efforts and allows the users to get to the right place at the right time • Altogether AH techniques can significantly improve the effectiveness of hypertext and hypermedia systems
  25. 25. THM2: AH is best of both worlds • The Artificial Intelligent approach: machine intelligence makes a decision for a human – Adaptive NL generation, sequencing • The HCI approach: human intelligence is empowered to make a decision – Classic stretchtext and hypertext • Adaptive hypermedia: human intelligence and AI collaborate in making a decision
  26. 26. Adaptive Web UM ITSHT 1G AH 2G AH 3G AH IR/IFSearch, User Diversity Social Navigation Classic Adaptive Hypermedia Adaptive Web Mobile Adaptive Web UbiComp Context Modeling Affective Computing 1995-2002
  27. 27. Adaptive Web: Why? Different people are different Individuals are different at different times "Lost in hyperspace” Large variety of users Variable characteristics of the users Large hyperspace
  28. 28. Adaptive Hypermedia Goes Web • Implementation of classic technologies in classic application areas on the new platform (but more techniques) • New search-related technologies • New user modeling challenges • Integrated adaptive systems • New application areas
  29. 29. Adaptive hypermedia technologies Adaptive presentation Adaptive navigation support Direct guidance Adaptive link sorting Adaptive link hiding Adaptive link annotation Adaptive link generation Adaptive multimedia presentation Adaptive text presentation Adaptation of modality Canned text adaptation Natural language adaptation Inserting/ removing fragments Altering fragments Stretchtext Sorting fragments Dimming fragments Map adaptation Hiding Disabling Removal
  30. 30. InterBook: Web-Based AH • An authoring shell and a delivery system for Web-based electronic textbooks • Explores several adaptive navigation support technologies • Oriented towards Web-based education needs
  31. 31. Adaptive annotation in InterBook 1. State of concepts (unknown, known, ..., learned) 2. State of current section (ready, not ready, nothing new) 3. States of sections behind the links (as above + visited) 3 2 1 √
  32. 32. Bookshelves and books
  33. 33. Book view
  34. 34. Glossary view
  35. 35. Goal-based learning: “help” and “teach this”
  36. 36. Results • No overall difference in performance • Sequential navigation dominates ...but ... • Adaptive annotation encourage non- sequential navigation • Helps to those who follow suggestions • The adaptation mechanism works well
  37. 37. THM3: AH is not a Silver Bullet • A viewpoint: AH is an alternative to user- centered design. No need to study the user - we will adapt to everyone • The truth: – AH is a powerful HCI tool - as mouse, visualization, VR – We need to study our users and apply all usual range of usability techniques - we just have one more tool to use in our repository
  38. 38. The Need to Find It • Background – Adaptive Information Retrieval and Filtering – Machine Learning • Old techniques – Guidance: WebWatcher – Annotation: Syskill and Webert, MovieLens • New technique – Recommendation (link generation): Letizia, FAB, SiteIF
  39. 39. THM4: Not all adaptive Web systems are adaptive hypermedia • Many IR and IF filtering systems use an old search - oriented IR approach – No real hyperspace, no browsing, no AH • Most of advanced recommenders use simple 1-D adaptive hypermedia techniques - guidance, sorting, generation • Power of a recommendation engine could be enhanced by power of a proper interface
  40. 40. User Modeling Challenges • Low bandwidth for user modeling – Extended user feedback • Rating, bookmarking, dowloading, purchasing… – Collaborative filtering and Social navigation • GroupLens, FireFly, FootSteps, … Amazon.com – Integrated Systems • Wider variety of users – Adapting to disabled users: AVANTI – Adapting to learning styles: INSPIRE
  41. 41. Application Areas: Old and New • Web-based education • InterBook, ELM-ART, AHA!, KBS-Hyperbook, MANIC • On-line information systems • PEBA-II, AVANTI, SWAN, ELFI, MovieLens • Information retrieval, filtering, recommendation • SmartGuide, Syskill & Webert, IfWeb, SiteIF, FAB, AIS • E-commerce • Tellim, SETA, Adaptive Catalogs, …, Amazon.com • Virtual museums • ILEX, Power, Marble Museum, SAGRES • Performance Support Systems
  42. 42. Integrated Adaptive Web Systems • Integrate several “systems”, traditionally independent, inside one Web application • Several user modeling and adaptation techniques, one user model • Better value for users • Improved quality of user modeling
  43. 43. Exploring Integrated Systems • ELM-ART (1996-1998) - integrated ITS for LISP programming • ADAPTS (1998-1999) - integrated performance support systems for avionics technicians • KnowledgeTree (2000-2003) - integrated architecture for E-Learning • CUMULATE (2002-2003) - centralized user/student modeling server
  44. 44. Adaptive Information Services • Early prototypes: Basaar, FAB, ELFI • Integrates content-based and collaborative technologies • Integrates search and filtering • Integrates user-driven and adaptive personalization • Example: http://www.n24.de
  45. 45. ELM-ART: Integrated Web- based Adaptive Educational System • Model: adaptive electronic textbook – hierarchical textbook – tests – examples – problems – programming laboratory • Extra for Web-based teaching – messages to the teacher – chat room
  46. 46. Adaptivity in ELM-ART • Adaptive navigation support • Adaptive sequencing • Adaptive testing • Adaptive selection of relevant examples • Adaptive similarity-based navigation • Adaptive program diagnosis
  47. 47. ANS + Adaptive testing
  48. 48. Adaptive Diagnostics
  49. 49. Similarity-Based Navigation
  50. 50. Architecture for integration of: – Diagnostics – Technical Information – Performance-oriented Training  A demonstration for “Best of both worlds” case: Human and Artificial intelligences work together ADAPTS ADAPTS: Integrated Adaptive Performance Support IETMs Training Diagnostics
  51. 51. Video clips (Training) Schematics Engineering Data Theory of operation Block diagrams Equipment Simulations (Training) Equipment Photos Illustrations Troubleshooting Step Troubleshooting step plus hypermedia support information, custom-selected for a specific technician within a specific work context. ADAPTS dynamically assembles custom-selected content. What’s in adaptive IETM?
  52. 52. UserModel Diagnostics Content Navigation What task to doSystem health What content is applicable to this task and this user Levels of detail How to display this content to this user Experience, Preferences, ASSESSES: DETERMINES: Adaptive Diagnostics Personalized Technical Support
  53. 53. The result Maintenance history Preprocessed, condition-based inputs Technician and Operator Observations Sensor inputs (e.g., 1553 bus) Personalized Display IETM Training Stretch text OutlineLinks Training records Skill assessment Experience Preferences Content NavigationDiagnostics How do we make decisions? User Model
  54. 54. Integrated interface
  55. 55. THM5: Not all areas are ready for the Adaptive Web • An attempt to implement adaptive Web-based education in Carnegie Technology Education • What is the difference between the success in ADAPTS and the failure at Carnegie Technology Education? • An application area should be ready for it – Adaptivity offers benefits – Adaptivity has it cost – Users should be ready and costs should be justified
  56. 56. Mobile Adaptive Web UM ITSHT 1G AH 2G AH 3G AH IR/IFSearch, User Diversity Social Navigation Classic Adaptive Hypermedia Adaptive Web Mobile Adaptive Web UbiComp Context Modeling Affective Computing 1997-2005?
  57. 57. The Need to Be Mobile • Background – Technology: wearables, mobiles, handhelds… – GIS and GPS work – HCI: Ubiquitous Computing • Need to adapt to the platform – Screen, computational power, bandwidth • New opportunities – Taking into account location/time/other context – Sensors and affective computing
  58. 58. New Application Areas • Mobile handheld guides – Museum guides: HYPERAUDIO, HIPS – City guides: GUIDE • Mobile recommenders – News and entertainment recommender • http://www.adaptiveinfo.com • Adaptive mobile information sites – ClixSmart Navigator • http://www.changingworlds.com/
  59. 59. 4th Generation? 1G AH 2G AH 3G AH IR/IFSearch, User Diversity Social Navigation Classic Adaptive Hypermedia Adaptive Web Mobile Adaptive Web UbiComp Context Modeling Affective Computing 4G AH ??? ??????
  60. 60. 3D Web • Web is not 2D anymore - it includes a good amount of VR content • 3D offers more power and supports some unique ways to access information • 3D Web as the future of the Web? • The dream of an immersive Web: – Neal Stephenson: Metaverse (Snow Crash) – Victor Lukyanenko: The Depth (Mirrors)
  61. 61. Adaptive 3D Web? • Motivated by a pioneer work… – Luca Chittaro and Roberto Ranon Adding adaptive features to virtual reality interfaces for ecommerce, in Proc. Adaptive Hypermedia and Adaptive Web-based Systems, AH2000, p. 86-91. • VR as “another” virtual space with user- directed navigation • Same ideas of adaptive presentation and adaptive navigation support can be explored • Support is more important (UI problems)!
  62. 62. Adaptive Navigation Support in 3D • Joint work with Stephen Hughes, Michael Lewis, Jeffrey Jacobson, SIS Usability Lab • How to guide the user to the appropriate information in a 3D space? • Possible applications: – VR Museum, E-commerce, E-learning • Guidance for 3D “Attentive navigation” – Direct guidance with different levels of control – Annotation - combination of freedom and guidance
  63. 63. More information... • Adaptive Hypertext and Hypermedia Home Page: http://wwwis.win.tue.nl/ah/ • Brusilovsky, P., Kobsa, A., and Vassileva, J. (eds.) (1998), Adaptive Hypertext and Hypermedia. Dordrecht: Kluwer Academic Publishers • Special Issue of Communications of the ACM on Adaptive Web: May 2002, vol. 45, Number 5 • Adaptive Hypermedia and User Modeling Conference Series (look for proc. in Springer-Verlag’s LNCS/LNAI) • Most recent Adaptive Hypermedia 2004 in Eindhoven

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