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Table of Contents
Preface; Contents; Introduction; 1 A Survey of Cognitive Assistants; 1.1 Introduction; 1.2 Cognitive Assistants; 1.2.1 DayGuide; 1.2.2 Active@Home; 1.2.3 CoME; 1.2.4 DALIA; 1.2.5 EDLAH2; 1.2.6 iGenda; 1.2.7 M3W; 1.2.8 MyGuardian; 1.2.9 PersonAAL; 1.3 Conclusion; References; Reasoning; 2 Argumentation-Based Personal Assistants for Ambient Assisted Living; 2.1 Introduction; 2.2 Decision-Making and Recommendation; 2.3 Computational Persuasion; 2.4 Conclusion and Open Issues; References; 3 Kidney Care-A Personal Assistant Assessment; Abstract; 3.1 Introduction.
3.2 Knowledge Representation and Reasoning3.2.1 Quantitative Knowledge; 3.2.2 Qualitative Knowledge; 3.3 A Case Based Approach to Problem Solving; 3.4 System's Architecture; 3.5 Case Study; 3.5.1 Data Processing; 3.5.2 The CBR Approach to Computing; 3.6 Conclusion; Acknowledgements; References; Health; 4 Visual Working Memory Training of the Elderly in VIRTRAEL Personalized Assistant; Abstract; 4.1 Introduction; 4.2 Related Work; 4.3 VIRTRAEL Description; 4.4 Classification and Memorization of Images Exercise; 4.4.1 Pilot Study; 4.4.2 Personalization of the Exercise.
4.5 Conclusions and Future WorkReferences; 5 Personal Robot Assistants for Elderly Care: An Overview; 5.1 Introduction; 5.2 Assistive Social Robots; 5.2.1 Companion Robots; 5.2.2 Service Robots; 5.3 Conclusions; References; Personalization; 6 Personalized Visual Recognition via Wearables: A First Step Toward Personal Perception Enhancement; Abstract; 6.1 Introduction; 6.2 Related Work; 6.3 Personalized Visual Recognition System via Google Glass; 6.3.1 System Architecture; 6.3.2 Client; 6.3.3 Server; 6.3.4 Workflow; 6.3.5 Training; 6.4 Classification; 6.5 Experiment 1: Person Identification.
6.5.1 Overview6.5.2 Training Data; 6.5.3 Finetuning for 20-Class Person Identification; 6.5.4 Chained Finetuning for 5-Class Person Identification; 6.5.5 Comparison Between Finetuning and Chained Finetuning; 6.6 Experiment 2: Object Recognition; 6.6.1 Overview; 6.6.2 Training and Validation Data; 6.6.3 Chained Finetuning for 10-Class Object Recognition; 6.7 Discussion and Future Work; 6.8 Conclusion; Acknowledgements; References; 7 Intelligent Personal Assistant for Educational Material Recommendation Based on CBR; Abstract; 7.1 Introduction; 7.2 Preliminaries.
7.2.1 Learning Objects (LO), Learning Objects Repositories and Repository Federation7.2.2 Case-Based Reasoning (CBR); 7.2.3 Recommender Systems; 7.2.4 Student Profile; 7.3 Related Works; 7.4 Proposed Model; 7.4.1 CBR Stages in Intelligent Personal Assistant to Recommend Educational Resources; 7.5 Experiments and Results; 7.5.1 Study Case; 7.6 Conclusions; Acknowledgements; References; Robotics; 8 Characterize a Human-Robot Interaction: Robot Personal Assistance; 8.1 Introduction; 8.2 Theoretical Foundations; 8.2.1 Social Robots; 8.2.2 Personal Assistance; 8.3 The Proposed Design; 8.3.1 Dynamic HRI Monitoring Architecture.
3.2 Knowledge Representation and Reasoning3.2.1 Quantitative Knowledge; 3.2.2 Qualitative Knowledge; 3.3 A Case Based Approach to Problem Solving; 3.4 System's Architecture; 3.5 Case Study; 3.5.1 Data Processing; 3.5.2 The CBR Approach to Computing; 3.6 Conclusion; Acknowledgements; References; Health; 4 Visual Working Memory Training of the Elderly in VIRTRAEL Personalized Assistant; Abstract; 4.1 Introduction; 4.2 Related Work; 4.3 VIRTRAEL Description; 4.4 Classification and Memorization of Images Exercise; 4.4.1 Pilot Study; 4.4.2 Personalization of the Exercise.
4.5 Conclusions and Future WorkReferences; 5 Personal Robot Assistants for Elderly Care: An Overview; 5.1 Introduction; 5.2 Assistive Social Robots; 5.2.1 Companion Robots; 5.2.2 Service Robots; 5.3 Conclusions; References; Personalization; 6 Personalized Visual Recognition via Wearables: A First Step Toward Personal Perception Enhancement; Abstract; 6.1 Introduction; 6.2 Related Work; 6.3 Personalized Visual Recognition System via Google Glass; 6.3.1 System Architecture; 6.3.2 Client; 6.3.3 Server; 6.3.4 Workflow; 6.3.5 Training; 6.4 Classification; 6.5 Experiment 1: Person Identification.
6.5.1 Overview6.5.2 Training Data; 6.5.3 Finetuning for 20-Class Person Identification; 6.5.4 Chained Finetuning for 5-Class Person Identification; 6.5.5 Comparison Between Finetuning and Chained Finetuning; 6.6 Experiment 2: Object Recognition; 6.6.1 Overview; 6.6.2 Training and Validation Data; 6.6.3 Chained Finetuning for 10-Class Object Recognition; 6.7 Discussion and Future Work; 6.8 Conclusion; Acknowledgements; References; 7 Intelligent Personal Assistant for Educational Material Recommendation Based on CBR; Abstract; 7.1 Introduction; 7.2 Preliminaries.
7.2.1 Learning Objects (LO), Learning Objects Repositories and Repository Federation7.2.2 Case-Based Reasoning (CBR); 7.2.3 Recommender Systems; 7.2.4 Student Profile; 7.3 Related Works; 7.4 Proposed Model; 7.4.1 CBR Stages in Intelligent Personal Assistant to Recommend Educational Resources; 7.5 Experiments and Results; 7.5.1 Study Case; 7.6 Conclusions; Acknowledgements; References; Robotics; 8 Characterize a Human-Robot Interaction: Robot Personal Assistance; 8.1 Introduction; 8.2 Theoretical Foundations; 8.2.1 Social Robots; 8.2.2 Personal Assistance; 8.3 The Proposed Design; 8.3.1 Dynamic HRI Monitoring Architecture.