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E-raamat: Human-Centred Web Adaptation and Personalization: From Theory to Practice

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Human-Centred Web Adaptation and Personalization: From Theory to PracticeSuurem pilt
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This book focuses on the importance of adaptation and personalization in todays society and the upgraded role computational systems and the Internet play in our day-to-day activities. In this era of wireless communication, pervasive computing and the Internet of Things, it is becoming increasingly critical to ensure humans remain central in the developmental process of new technologies to guarantee their continued usefulness and a positive end-user experience.

Organized into three clear parts - theory, principles and practice, a holistic approach to designing and developing adaptive interactive systems and services has been adopted. With an emphasis on distinct human factors, both basic and applied research topics are explored, extending from human-centred user models, driven by users individual differences in cognitive processing and emotions, to the creation of smart interfaces that can handle the ever increasing volume and complexity of information to thebenefit of the end-user.



Human-Centred Web Adaptation and Personalization From Theory to Practice is meticulously crafted to serve researchers, practitioners, and students who wish to have an end-to-end understanding of how to convert pure research and scientific results into viable user interfaces, system components and applications. It will serve to bridge the knowledge gap that still remains by suggesting interaction design and implementation guidelines for areas like E-Commerce, E-Learning and Usable Security.   

Arvustused

This book covers a very new and interesting topic of improving user interfaces (UIs) by making them friendly to each particular user. The reader can find a lot of information about the history of UIs and the current ways to make them more efficient. There are also hundreds of references, which will provide the reader with details from many fields. The book is useful for researchers who would like to study many aspects of the field. (Claudiu Popescu, Computing Reviews, April, 2017)

Part I Theory: The Human in the Centre of Web Personalization
1 Personalization in the Digital Era
3(24)
1.1 Introduction
3(2)
1.2 Rethinking Human-Computer Interaction
5(8)
1.2.1 Repositioning the "I" in HCI
7(2)
1.2.2 HCI Meets Adaptation and Personalization: Influential Research Disciplines
9(4)
1.3 The Need for User-Centred Design in Interactive Computing Systems and Interfaces
13(2)
1.4 The Concept of Web Adaptation and Personalization
15(5)
1.5 Current Problems and Challenges: An 'Out-of-the-Box' Thinking
20(3)
1.6 Summary
23(1)
References
24(3)
2 Human Factors in Web Adaptation and Personalization
27(52)
2.1 Introduction
27(3)
2.2 Human Cognition and Information Processing
30(23)
2.2.1 The Role of Human Memory
32(5)
2.2.2 Visual Perception
37(1)
2.2.3 Visual Search
38(3)
2.2.4 Visual Attention, Speed and Control of Processing
41(3)
2.2.5 Learning Styles
44(2)
2.2.6 Cognitive Styles
46(2)
2.2.7 Elicitation Methods of High-Level and Elementary Cognitive Processes
48(3)
2.2.8 Implication of Cognitive Aspects on Adaptation and Personalization
51(2)
2.3 Emotions and Learning Process
53(14)
2.3.1 Emotion Regulation
56(5)
2.3.2 Emotional Arousal
61(2)
2.3.3 Methods of Extracting Emotions and Anxiety
63(2)
2.3.4 Implications of Anxiety in Adaptive Interactive Environments
65(2)
2.4 Summary
67(1)
References
68(11)
Part II Principles: Web Adaptation and Personalization Processes and Techniques
3 User Modeling
79(24)
3.1 Introduction
79(2)
3.2 User Modeling Factors for Personalization
81(6)
3.2.1 User Information
81(4)
3.2.2 Context Information
85(2)
3.3 User Data Collection Methods
87(1)
3.3.1 Explicit User Data Collection Methods
87(1)
3.3.2 Implicit User Data Collection Methods
87(1)
3.4 User Model Generation
88(4)
3.4.1 Clustering
89(1)
3.4.2 Classification
90(1)
3.4.3 Association Discovery
91(1)
3.4.4 Sequential Pattern Mining
91(1)
3.5 Modeling Human Factors in Interactive Systems
92(5)
3.5.1 Identifying Intrinsic Human Factors for Building a Comprehensive User Model
93(4)
3.6 Summary
97(1)
References
98(5)
4 Personalization Categories and Adaptation Technologies
103(34)
4.1 Introduction
103(3)
4.2 Personalization Categories
106(4)
4.2.1 Link Personalization
106(1)
4.2.2 Content Personalization
106(1)
4.2.3 Personalized Web Search
107(1)
4.2.4 Context Personalization
107(1)
4.2.5 Authorized Personalization
108(1)
4.2.6 Humanized Personalization
109(1)
4.3 Adaptation Technologies
110(5)
4.3.1 User Customization
110(1)
4.3.2 Rule-Based Filtering
110(1)
4.3.3 Content-Based Filtering
111(1)
4.3.4 Collaborative Filtering
111(1)
4.3.5 Web Mining
112(1)
4.3.6 Demographic-Based Filtering
113(1)
4.3.7 Agent Technology
114(1)
4.3.8 Cluster Models
114(1)
4.4 Semantic Web Technologies for Adaptation and Personalization Systems
115(2)
4.5 Leveraging the Social Web for Adaptation and Personalization
117(1)
4.6 Adaptation Effects in User Interfaces
118(2)
4.6.1 Adaptive Content Presentation
118(1)
4.6.2 Adaptive Navigation Support
119(1)
4.7 Web Adaptation and Personalization Systems and Frameworks
120(8)
4.7.1 PAC
121(1)
4.7.2 PersonaWeb
121(1)
4.7.3 Hybreed
121(1)
4.7.4 Adaptive Notifications in Virtual Communities
122(1)
4.7.5 Smartag
122(1)
4.7.6 PRESYDIUM
122(1)
4.7.7 PERSONAF
123(1)
4.7.8 CTRL
123(1)
4.7.9 EKPAIDEION
123(1)
4.7.10 AdaptiveWeb
124(1)
4.7.11 Knowledge Sea II
124(1)
4.7.12 CUMAPH
124(1)
4.7.13 mPERSONA
125(1)
4.7.14 INSPIRE
125(1)
4.7.15 SQL-Tutor
125(1)
4.7.16 Proteus
126(1)
4.7.17 WBI
126(1)
4.7.18 ARCHIMIDES
126(1)
4.7.19 TANGOW
127(1)
4.7.20 AHA!
127(1)
4.7.21 SKILL
127(1)
4.7.22 ELM-ART II
128(1)
4.7.23 BASAR
128(1)
4.7.24 InterBook
128(1)
4.8 Summary
128(2)
References
130(7)
5 A Generic Human-Centred Personalization Framework: The Case of mapU
137(48)
5.1 Introduction
137(3)
5.2 A High-Level Adaptation and Personalization Architecture
140(1)
5.3 Conceptual Design of mapU
141(18)
5.3.1 Module 1: User Modeling
143(12)
5.3.2 Module 2: Personalization
155(4)
5.4 Design and Development of mapU
159(14)
5.4.1 mapU Web Server
159(13)
5.4.2 mapU Back-End
172(1)
5.5 Technologies and Languages for the Design and Development of the mapU System
173(6)
5.5.1 HTML: HyperText Markup Language
173(1)
5.5.2 CSS (Cascade Style Sheets): Giving Style to HTML
174(1)
5.5.3 Client-Side Languages
175(1)
5.5.4 Server-Side Languages and Frameworks
176(3)
5.5.5 Storing and Retrieving Data
179(1)
5.6 Summary
179(1)
References
180(5)
Part III Practice: A Practical Guide and Empirical Evaluation in Three Distinct Application Areas
6 The E-Learning Case
185(50)
6.1 Introduction
185(10)
6.1.1 Potential, Limitations and a High-Level Classification of E-Learning Systems
187(3)
6.1.2 Context-Aware and Activity-Based Considerations in E-Learning Environments
190(2)
6.1.3 The Importance of Adapting and Personalizing E-Learning Environments
192(3)
6.2 Design Considerations and Constraints
195(2)
6.3 Human-Centred Design Guidelines
197(17)
6.3.1 Guidelines for E-Learning Environments
199(8)
6.3.2 Guidelines for M-Learning Environments
207(4)
6.3.3 Adaptation Paradigm in mapU Based on Guidelines
211(3)
6.4 Evaluation
214(12)
6.4.1 Method of Study 1: Eye-Tracking Study
215(2)
6.4.2 Method of Study 2: Personalized E-Learning Study
217(3)
6.4.3 Method of Study 3: Personalized M-Learning Study
220(1)
6.4.4 Results
220(6)
6.5 Benefits, Impact and Limitations
226(2)
6.6 Summary
228(1)
References
229(6)
7 The E-Commerce Case
235(52)
7.1 Introduction
235(8)
7.1.1 Potential and Limitations of Multi-channel E-Commerce Products and Services Delivery
237(3)
7.1.2 Why to Adapt and Personalize E-Commerce Environments
240(3)
7.2 Design Considerations and Constraints
243(3)
7.3 Human-Centred Design Guidelines
246(17)
7.3.1 Guidelines for E-Commerce Product Views
249(10)
7.3.2 Guidelines for E-Commerce Checkout Process
259(2)
7.3.3 Adaptation Paradigm in mapU Based on Guidelines
261(2)
7.4 Evaluation of Product Views Personalization (Based on Sony Design)
263(7)
7.4.1 Methodology
264(1)
7.4.2 Results
265(5)
7.5 Evaluation of Product Views Personalization (Based on HP Design)
270(5)
7.5.1 Methodology
271(1)
7.5.2 Results
272(3)
7.6 Evaluation of Checkout Process Personalization
275(4)
7.6.1 Methodology
276(1)
7.6.2 Results
277(2)
7.7 Benefits, Impact and Limitations
279(3)
7.8 Summary
282(1)
References
283(4)
8 The Usable Security Case
287(44)
8.1 Introduction
287(7)
8.1.1 User Authentication
289(2)
8.1.2 Human Interaction Proofs (CAPTCHA)
291(2)
8.1.3 Why to Adapt and Personalize Security-Related Tasks
293(1)
8.2 Design Considerations and Constraints
294(5)
8.2.1 Design Considerations in Knowledge-Based User Authentication
294(2)
8.2.2 Security Considerations in Knowledge-Based User Authentication
296(1)
8.2.3 Design Considerations in CAPTCHA
297(2)
8.2.4 Security Considerations in CAPTCHA
299(1)
8.3 Human-Centred Design Guidelines
299(14)
8.3.1 User Authentication Mechanisms
302(5)
8.3.2 CAPTCHA Mechanisms
307(4)
8.3.3 Adaptation Paradigm in mapU Based on Guidelines
311(2)
8.4 Evaluation
313(9)
8.4.1 Study Design Methodology
313(2)
8.4.2 Participants
315(1)
8.4.3 User Interaction Metrics
315(1)
8.4.4 Hypotheses
316(1)
8.4.5 Analysis of Results
316(6)
8.5 Benefits, Impact and Limitations
322(2)
8.6 Summary
324(1)
References
325(6)
Epilogue 331
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