Phenotropic Interaction: Improving Interfaces with Computing with Words and Perceptions (Fuzzy Management Methods)

Foreword
Preface
Acknowledgments
Contents
Acronyms
List of Figures
List of Tables
List of Algorithms
Part I Motivation and Objectives
	1 Introduction
		1.1 Background and Motivation
		1.2 Research Objectives
		1.3 Methodology
			1.3.1 Design Science Research
			1.3.2 Toward Antidisciplinary Research
		1.4 Outline
		1.5 Own Research Contribution
		References
Part II Theory of Naturalness
	2 Phenotropic Interaction
		2.1 Phenotropics
		2.2 Design Principles of Phenotropic Interaction
		2.3 Phenotropic Interaction Framework
		2.4 Concluding Remarks
		References
	3 Cognitive and Perceptual Computing
		3.1 Conversation Theory
		3.2 Computing with Words and Perceptions
		3.3 Automated Reasoning
		3.4 Interactive Machine Learning
		3.5 Explainable Artificial Intelligence
		3.6 Concluding Remarks
		References
Part III Natural Language Conversations
	4 Semantic Similarity Measures
		4.1 Conceptual Similarity Measures
		4.2 Spectral Similarity Measures
		4.3 A Novel Spectral Similarity Measure
			4.3.1 Choice of Knowledge Base
			4.3.2 Spectral Semantic Similarity Measure
		4.4 Practical Implementation Challenges
			4.4.1 Thesaurus Selection
			4.4.2 Multiple Meanings
			4.4.3 Order of Synonymy
		4.5 Evaluation
			4.5.1 Methodology
			4.5.2 Results
		4.6 Concluding Remarks
		References
	5 Automatic Precisiation of Meaning
		5.1 Automatic Precisiation of Meaning 1.0
			5.1.1 Basis Selection and Precisiation
			5.1.2 The APM 1.0 Algorithm
		5.2 Automatic Precisiation of Meaning 2.0
			5.2.1 Algorithm Choices
			5.2.2 The APM 2.0 Algorithm
		5.3 Evaluation
			5.3.1 Methodology
			5.3.2 Results
		5.4 Concluding Remarks
		References
	6 Fuzzy Analogical Reasoning
		6.1 Analogical Reasoning
		6.2 The FAR Prototype
			6.2.1 Conceptual Analogies
			6.2.2 Spectral Analogies
			6.2.3 Prototype Interface
		6.3 Evaluation
			6.3.1 Methodology
			6.3.2 Results
		6.4 Concluding Remarks
		References
Part IV Applications of Phenotropic Interaction
	7 Phenotropic Interaction in Virtual Assistants
		7.1 Extension of If This Then That Rules
			7.1.1 Query Preprocessing
			7.1.2 Query Matching
			7.1.3 Rule Adaptation with Fuzzy Analogical Reasoning
		7.2 The FVA Prototype
		7.3 Evaluation
			7.3.1 Methodology
			7.3.2 Results
		7.4 Concluding Remarks
		References
	8 Phenotropic Interaction in Smart Cities
		8.1 Jingle Jungle Maps
			8.1.1 Problem Statement
			8.1.2 Architecture
			8.1.3 Evaluation
			8.1.4 Phenotropic Interaction
		8.2 Streetwise
			8.2.1 Problem Statement
			8.2.2 Architecture
			8.2.3 Evaluation
			8.2.4 Phenotropic Interaction
		8.3 Concluding Remarks
		References
Part V Conclusions
	9 Outlook and Conclusions
		9.1 Summary
		9.2 Alignment with Research Questions
		9.3 Future Developments
		9.4 Outlook and Conclusions
		Reference
Glossary
A Survey: Ordering of Scalar Terms
B Semantic Similarity Evaluation Details
C Evaluation of the FVA Prototype