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Intelligent User Interfaces: Adaptation and Personalization Systems and Technologies

Book Description

Intelligent User Interfaces: Adaptation and Personalization Systems and Technologies innovatively combines broad research areas in intelligent user interfaces to provide an authoritative, comprehensive review of recent studies, state-of-the-art applications, and new methodologies and theories that support the issue of adaptation and personalization in various application levels.

Table of Contents

  1. Copyright
  2. Editorial Advisory Board
  3. Foreword
  4. Preface
  5. Acknowledgment
  6. Theoretical Aspects of Adaptive and Personalized User Interfaces
    1. An Assessment of Human Factors in Adaptive Hypermedia Environments
      1. ABSTRACT
      2. INTRODUCTION
      3. ADAPTIVE HYPERMEDIA OVERVIEW
      4. WEB PERSONALIZATION OVERVIEW
      5. SIMILARITIES AND DIFFERENCES
      6. THE USER PROFILE IMPERATIVE
      7. CONSIDERING THE IMPORTANCE OF HUMAN FACTORS IN FURTHER COMPLETING THE USER PROFILE
      8. A DATA-IMPLICATIONS CORRELATION DIAGRAM
      9. OVERVIEWING AN ADAPTIVE WEB ARCHITECTURE AND THE COMPREHENSIVE USER PROFILE CONSTRUCTION
      10. EXPERIMENTAL EVALUATION
      11. DISCUSSION AND CONCLUSION
      12. FUTURE RESEARCH DIRECTIONS
      13. REFERENCES
      14. ADDITIONAL READING
      15. ENDNOTE
    2. Case Studies in Adaptive Information Access: Navigation, Search, and Recommendation
      1. ABSTRACT
      2. INTRODUCTION
      3. CASE-STUDY 1: INTELLIGENT NAVIGATION IN MOBILE PORTALS
      4. CASE-STUDY 2: COMMUNITY-BASED PERSONALIZATION FOR WEB SEARCH
      5. CASE-STUDY 3: DYNAMIC CRITIQUING IN PRODUCT RECOMMENDATION
      6. CONCLUSION
      7. FUTURE RESEARCH DIRECTIONS
      8. ACKNOWLEDGMENT
      9. REFERENCES
      10. ADDITIONAL READING
    3. The Effects of Human Factors on the Use of Web-Based Instruction
      1. ABSTRACT
      2. INTRODUCTION
      3. THEORECTICAL FRAMEWORK
      4. RESEARCH DESIGN
      5. DISCUSSION RESULTS
      6. CONCLUSION
      7. REFERENCES
    4. The Next Generation of Personalization Techniques
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. DATA PREPERATION: ONTOLOGY LEARNING, EXTRACTION AND PRE-PROCESSING
      5. NATURAL LANGUAGE PROCESSING (NLP)
      6. USER MODELLING WITH SEMANTIC DATA
      7. ONTOLOGY-BASED RECOMMENDER SYSTEMS
      8. CONCLUSION AND FUTURE WORK
      9. REFERENCES
      10. ADDITIONAL READING
  7. Adaptive Content and Services
    1. Advanced Middleware Architectural Aspects for Personalised Leading-Edge Services
      1. ABSTRACT
      2. INTRODUCTION
      3. PERSONALISATION ASPECTS AND EVOLUTION FROM STATE OF THE ART
      4. MIDDLEWARE ARCHITECTURES AND SOLUTIONS FOR PERSONALISED SERVICE OFFERING
      5. ADVANCED CONCEPTS IN PERSONALISED SERVICE PROVISION
      6. CONCLUSION
      7. FUTURE RESEARCH DIRECTIONS
      8. REFERENCES
      9. ADDITIONAL READING
    2. Intelligent Information Personalization: From Issues to Strategies
      1. ABSTRACT
      2. INTRODUCTION: INFORMATION PERSONALIZATION
      3. FACETS OF INFORMATION PERSONALIZATION
      4. INTELLIGENT INFORMATION PERSONALIZATION ISSUES
      5. ADWISE: A FRAMEWORK FOR INTELLIGENT INFORMATION PERSONALIZATION
      6. PERSONALIZING MUSIC PLAYLISTS: A COMPOSITIONAL ADAPTATION APPROACH
      7. PERSONALIZING RECOMMENDATION OF NEWS ITEMS: A CONSTRAINT SATISFACTION APPROACH
      8. PERSONALIZING HEALTHCARE INFORMATION: A BEHAVIOURAL MODELLING APPROACH
      9. CONCLUSION
      10. FUTURE RESEARCH DIRECTIONS
      11. REFERENCES
      12. ADDITIONAL READING
    3. A Semantically Adaptive Interface for Measuring Portal Quality in E-Government
      1. ABSTRACT
      2. INTRODUCTION
      3. RELATED WORK
      4. MOTIVATION
      5. SOLUTION DESCRIPTION
      6. CONCLUSION AND FUTURE WORK
      7. FUTURE RESEARCH DIRECTIONS
      8. REFERENCES
      9. ADDITIONAL READING
    4. Ontology-Based Personalization of E-Government Services
      1. ABSTRACT
      2. INTRODUCTION
      3. RELATED WORK
      4. PERSONALIZED ACCESS TO E-GOVERNMENT RESOURCES
      5. IMPLEMENTATION AND PERFORMANCE EVALUATION
      6. CONCLUSION
      7. FUTURE RESEARCH DIRECTIONS
      8. REFERENCES
      9. FURTHER READINGS
      10. ENDNOTES
    5. Context and Adaptivity-Driven Visualization Method Selection
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. CONTEXT MODELING
      5. VISUALIZATION METHODS AND THEIR SELECTION
      6. FUTURE RESEARCH DIRECTIONS
      7. REFERENCES
      8. ADDITIONAL READING
  8. Adaptive Processing and Communication
    1. Integrating Semantic Knowledge with Web Usage Mining for Personalization
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. WEB USAGE MINING AND PERSONALIZATION
      5. REQUIREMENTS FOR SEMANTIC WEB USAGE MINING
      6. A FRAMEWORK FOR ONTOLOGY- BASED PERSONALIZATION
      7. CONCLUSION
      8. REFERENCES
    2. Adaptive Presentation and Scheduling of Media Streams on Parallel Storage Servers
      1. ABSTRACT
      2. INTRODUCTION
      3. THE ARCHITECTURE OF THE PARALLEL MEDIA SERVER
      4. THE PROPOSED SCHEDULING ALGORITHM
      5. ADAPTABILITY MANAGEMENT
      6. RELATED WORK
      7. CONCLUSION
      8. FUTURE RESEARCH DIRECTIONS
      9. REFERENCES
      10. ADDITIONAL READING
  9. Innovative Applications with Adaptive Behaviour
    1. Impact of Cognitive Style on User Perception of Dynamic Video Content
      1. ABSTRACT
      2. INTRODUCTION
      3. USER COGNITIVE STYLES
      4. MULTIMEDIA LEARNING: A PERCEPTUAL EXPERIENCE?
      5. PROCEDURE
      6. RESULTS AND DISCUSSION
      7. CONCLUSION
      8. FUTURE RESEARCH DIRECTIONS
      9. REFERENCES
      10. ADDITIONAL READING
    2. Building Digital Memories for Augmented Cognition and Situated Support
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. BUILDING AUGMENTED MEMORIES
      5. USER SUPPORT THROUGH AUGMENTED MEMORIES
      6. CONCLUSION
      7. FUTURE RESEARCH DIRECTIONS
      8. REFERENCES
      9. ADDITIONAL READING
    3. Open Learner Modelling as the Keystone of the Next Generation of Adaptive Learning Environments
      1. ABSTRACT
      2. INTRODUCTION
      3. THE E-LEARNING EDUCATIONAL MODEL
      4. THE LeAvtiveMath PROJECT AND SYSTEM
      5. THE EXTENDED LEARNER MODEL
      6. GENERIC OPEN LEARNER MODELLING
      7. EVALUATION OF OPEN LEARNER MODELLING
      8. FUTURE RESEARCH DIRECTIONS
      9. REFERENCES
      10. ADDITIONAL READING
    4. From E-Learning Tools to Assistants by Learner Modelling and Adaptive Behavior
      1. ABSTRACT
      2. TECHNOLOGY ENHANCED LEARNING: PROS AND CONS
      3. ADAPTIVITY AND SYSTEM'S ASSISTANCE AT WORK
      4. TECHNOLOGIES FOR SYSTEMS' ADAPTIVITY AND ASSISTANCE
      5. SYSTEMS' INTELLIGENCE IN E-LEARNING: PROS AND CONS
      6. TRANSFORMATION STEPS FROM LEARNING TOOLS TO ASSISTANTS
      7. SUMMARY AND CONCLUSION
      8. ACKNOWLEDGMENT
      9. REFERENCES
    5. Using Emotional Intelligence in Personalized Adaptation
      1. ABSTRACT
      2. INSIDE CHAPTER
      3. INTRODUCTION
      4. USING PERSONALIZED ADAPTATION IN LEARNING
      5. THE KEY PARADIGMS OF THE EQ AGENT SYSTEM
      6. IMPLEMENTATION OF THE EQ AGENT SYSTEM
      7. FINE ART PROFESSIONAL TRAINING: ACCADEMI@VINCIANA
      8. CONCLUSION
      9. ACKNOWLEDGMENT
      10. REFERENCES
      11. APPENDIX I: CASE STUDY
      12. APPENDIX II: USEFUL URLS
      13. APPENDIX III: FURTHER READING
  10. Security, Privacy, and Personalization
    1. Technical Solutions for Privacy-Enhanced Personalization
      1. ABSTRACT
      2. INTRODUCTION
      3. PRIVACY PRINCIPLES
      4. PRIVACY CONCERNS
      5. TECHNICAL SOLUTIONS FOR PRIVACY-ENHANCED PERSONALIZATION
      6. DISCUSSION
      7. SUMMARY AND FUTURE RESEARCH DIRECTIONS
      8. REFERENCES
      9. ADDITIONAL READING
  11. Compilation of References
  12. About the Contributors
  13. Index