Smart Tourism–The Impact of Artificial Intelligence and Blockchain (Intelligent Systems Reference Library, 249)

Foreword
	References
Preface
Contents
Acronyms
List of Figures
List of Tables
1 Introduction
	1.1 Research Objectives
	1.2 Book Structure
	References
2 Conceptualizing Smart Tourism
	2.1 Introduction
	2.2 Methodology and Research Approach
	2.3 Key Concepts and Approaches
		2.3.1 Theoretical Contribution and Literature Review
		2.3.2 Context Awareness
		2.3.3 Cultural Heritage
		2.3.4 Recommender Systems
		2.3.5 Social Media
		2.3.6 Internet of Things
		2.3.7 User Experience
		2.3.8 Real Time
		2.3.9 User Modelling
		2.3.10 Augmented Reality
		2.3.11 Artificial Intelligence
		2.3.12 Big Data
		2.3.13 Cyber Tourism
		2.3.14 Privacy and Data Protection
		2.3.15 Blockchain
	References
3 Mobile Applications in Smart Tourism and Smart Cities Based on Crowdsourcing
	3.1 Smart Cities
	3.2 Crowdsourcing: State of the Art
	3.3 Implementing Crowdsourcing in the Context of Smart Cities
		3.3.1 Mobile Crowdsourcing Application for Data Sharing
		3.3.2 Mobile Crowdsourcing Application for Signal Measuring
	3.4 Smartphone Crowdsourcing and Data Sharing Towards …
		3.4.1 Problem Setting and Inspiration
		3.4.2 System Architecture
	References
4 Mobile Applications in Smart Tourism: Implementing User Modelling
	4.1 User Modelling: History & State of Art
	4.2 Smart Tourism Through Social Network User Modeling
	4.3 Implementing User Modeling Utilising Implicit User Data
		4.3.1 Facebook
		4.3.2 Instagram
		4.3.3 Alternative Social Networking Applications for User Modelling
		4.3.4 Smartphone Context Awareness
		4.3.5 Semantic Web Technologies for Data Filtering
		4.3.6 Realizing Personalization: Application of the Analytic Hierarchy Process
		4.3.7 ProfileMe Framework: Research Overview
	4.4 Artificial Intelligence & User Modelling
	References
5 Artificial Intelligence in Smart Tourism
	5.1 Introduction
	5.2 Artificial Intelligence
	5.3 AI Autonomous Agents
	5.4 AI Smart Tourism Recommender Systems
	References
6 Implementing Machine Learning for Smart Tourism Frameworks
	6.1 Introduction
	6.2 Moments of Interest: A Smart Tourism Crowdsourcing Application
		6.2.1 Inspiration
		6.2.2 Moments of Interest: The Concept
		6.2.3 MOIs System Architecture
		6.2.4 Background Deep Learning Processing
		6.2.5 Conclusion
	6.3 Promoting Smart Tourism Personalised Services via a Combination …
		6.3.1 Inspiration
		6.3.2 Artificial Neural Networks
		6.3.3 Background Deep Learning Approaches
		6.3.4 Framework Architecture
		6.3.5 Model Development and Evaluation
		6.3.6 Conclusions and Future Directions
	References
7 Smart Tourism Embraces Blockchain
	7.1 Introduction
	7.2 The Blockchain Data Structure
	7.3 Types of Blockchains and Consensus Protocols
	7.4 Blockchain: Enabling the Smart Tourism Era
		7.4.1 Blockchain Enabled Services
		7.4.2 Blockchain Applications in Smart Tourism
	7.5 Proposed System Architecture
		7.5.1 Blockchain Module
		7.5.2 AI Recommendations, Context Awareness and Cybertourism
	References
8 Paving the Way for the Post-COVID-19 Era
	8.1 Literature Review and Critical Analysis
	References
9 Open Questions and Future Directions
	9.1 Introduction
		9.1.1 Applications
		9.1.2 Artificial Intelligence
		9.1.3 Blockchain
		9.1.4 Big Data
		9.1.5 Cyber Tourism and Metaverse
		9.1.6 Ethical and Privacy Considerations
		9.1.7 Social and Cultural Implications
		9.1.8 Government Initiatives
	References
10 Conclusions
	References