Personalized Human Computer Interaction 2nd Edition by Mirjam Augstein, Eelco Herder,Wolfgang Worndl 3110999609 9783110999600

Part I Foundations of personalization

Mark P. Graus, Bruce Ferwerda 1 Theory-grounded user modeling for personalized HCI

1.1 Introduction

1.2 Psychological models in personalization

1.3 The relationship between psychological traits and online behavior

1.4 Automated inference of psychological traits or styles

1.5 Incorporating psychological models in personalized systems

1.6 Combining trait inference and trait-based personalization

1.7 Conclusion

Jürgen Ziegler, Benedikt Loepp 2 User-centered recommender systems

2.1 Introduction

2.2 Presentation and visualization of recommendations

2.3 Preference elicitation and interactive control

2.4 Explaining recommendations

2.5 Evaluation of recommender systems

2.6 Summary and future directions

Markus Schedl, Elisabeth Lex 3 Fairness of information access systems

Acknowledgement

3.1 Introduction

3.2 Biases and fairness

3.3 Methods to mitigate harmful bias

3.4 Conclusions and open challenges

Part II User input and feedback

Mirjam Augstein, Thomas Neumayr 4 Personalization and user modeling for interaction processes

4.1 Introduction

4.2 Approach and methodology

4.3 Application areas of personalized interaction

4.4 Discussion and conclusions

Tobias Moebert, Jan N. Schneider, Dietmar Zoerner, Anna Tscherejkina, Ulrike Lucke 5 How to use socio-emotional signals for adaptive training

Acknowledgement

5.1 Introduction

5.2 The concept of emotions and human emotion recognition

5.3 Adaptivity on the example of the training of emotion recognition

5.4 The emotional state of the learner as a supporting parameter for adaptivity

5.5 Discussion

5.6 Conclusion

Dietmar Jannach, Michael Jugovac, Ingrid Nunes 6 Explanations and user control in recommender systems

6.1 Introduction

6.2 Explanations in recommender systems

6.3 Putting the user into control

6.4 Summary and future directions

Eelco Herder, Claus Atzenbeck 7 Feedback loops and mutual reinforcement in personalized interaction

7.1 Introduction

7.2 Computer-supported human decision-making

7.3 Mutual reinforcement in classical user modeling and HCI

7.4 Everyday recommendations from commercial providers

7.5 Integrating conscious decision-making into the interface

7.6 Discussion and future perspectives

Part III Personalization purposes and goals

Julio Abascal, Olatz Arbelaitz, Xabier Gardeazabal, Javier Muguerza, Ainhoa Yera 8 Personalizing the user interface for people with disabilities

Acknowledgement

8.1 Introduction

8.2 User modeling and personalized interaction for people with disabilities

8.3 Evolution and types of interface personalization for people with disabilities

8.4 Data collection and analysis for user modeling

8.5 User interface personalization for specific applications

8.6 Impact of interface personalization on the privacy of users with disabilities

8.7 Conclusions

Judith Masthoff, Julita Vassileva 9 Personalized persuasion for behavior change

9.1 Introduction

9.2 Theories

9.3 Behavior change frameworks and techniques and personalization

9.4 Application domains

9.5 Evaluation

9.6 Ethical issues of personalized persuasion

9.7 Summary and outlook

Chiara Luisa Schleu, Mirjam Augstein 10 Personalization approaches for remote collaborative interaction

Acknowledgement

10.1 Introduction

10.2 Background literature

10.3 Qualitative study

10.4 Thematic coding and taxonomy

10.5 Design implications

10.6 Discussion and conclusion

Appendix A Taxonomy

Part IV Personalization domains

Peter Knees, Markus Schedl, Bruce Ferwerda, Audrey Laplante 11 Listener awareness in music recommender systems: directions and current trends

Acknowledgement

11.1 Introduction

11.2 Relevant factors in music recommendation

11.3 Correlates of music preferences

11.4 Contextual and situational music listening behavior

11.5 Music information behavior

11.6 User-centric evaluation of music recommender systems

11.7 Conclusions

Daniel Herzog, Linus W. Dietz, Wolfgang Wörndl 12 Tourist trip recommendations – foundations, state of the art and challenges

12.1 Introduction

12.2 The tourist trip design problem

12.3 State of the art in tourist trip recommendations

12.4 Current and future challenges

12.5 Conclusions

Wilfried Grossmann, Mete Sertkan, Julia Neidhardt, Hannes Werthner 13 Pictures as a tool for matching tourist preferences with destinations

13.1 Introduction

13.2 Related work

13.3 The picture-based approach

13.4 Validity of the picture-based approach

13.5 Conclusions and further development