RESEARCH ON MODELS AND ALGORITHMS FOR ARGUMENTATION SUPPORT SYSTEMS
RESEARCH ON MODELS AND ALGORITHMS FOR ARGUMENTATION SUPPORT SYSTEMS
Caiquan Xiong
Hubei University of Technology
Copyright © 2024 by Cayley Nielson Press, Inc.
ISBN: 978-1-957274-21-8
Cayley Nielson Press Scholarly Monograph Series Book Code No.: 214-11-1
US$185.50
Preface
This book systematically presents the author's research on the Meta-Synthetic Methodology and its application in the design and development of an Integrated Platform for Argumentation Based on the Hall for Workshop of Meta-Synthetic Engineering (HWMSE). It begins by introducing the foundational concepts of the Meta-Synthetic Methodology, which emphasizes the combination of human and machine intelligence, with human cognition as the leading element, progressing from qualitative to quantitative synthesis.
Based on an analysis of the Meta-Synthetic Methodology and the characteristics of group thinking, the framework for a collaborative argumentation process within the HWMSE is proposed. This framework integrates human intuition and experience with computational tools, aiming to solve complex problems through a structured group discussion process.
The book then delves into argumentation models and algorithms, covering models for group intelligence emergence, persuasive argumentation, decision-making, and voting. These models are essential to supporting the meta-synthetic approach in both qualitative and quantitative dimensions. Furthermore, it addresses key technical challenges in designing and implementing an the environment of metasynthetic. These challenges include system architecture design, argumentation process control, argumentation information visualization, text segmentation and analysis, and intelligent data and information recommendations during argumentation processes.
This research was supported by several key projects, including the National Key R&D Program (Project No.2017YFC1405403), the National Natural Science Foundation (Project No.61075059), the Green Industry Science and Technology Leading Project of Hubei University of Technology (Product Development Category) (Project No. CPYF2017008). I am sincerely grateful for this support.
I extend my heartfelt gratitude to Professor Li Dehua of Huazhong University of Science and Technology for his invaluable guidance throughout the research and writing of this book. I am deeply thankful to my dedicated research team members—Zhan Yifan, Xiang Wuhua, Chen Chunyan, Li Xuan, Li Yuan, Lv Ke, Shen Li, Huang Ziwen, and Du Jiarong—for their significant contributions to specific research tasks and programming. My sincere appreciation also goes to the authors whose research works have been cited in this book.
Given the complexity of the subject and the author's limited expertise, there may be limitations in method selection and evaluation. I welcome feedback and corrections from readers.
Caiquan Xiong
Hubei University of Technology
Wuhan, Hubei, China
January 17, 2024
Contents
Preface I
1 Draft Consensus Building in Hall for Workshop of Meta-Synthetic Engineering 1
1.1 Introduction 1
1.2 Draft consensus 2
1.3Draft consensus model 5
1.3.1 Description of the problem 5
1.3.2 Consensus Building Graph (CBG) 6
1.3.3 Calculation of consensus 7
1.3.4 Principles of consensus building 8
1.4. Visualization of consensus building 9
1.5 Conclusions 10
2 A Discussion Information-Structuring Model Based on the Toulmin Formalism 12
2.1 Introduction 12
2.2 Toulmin argument structure 14
2.3 Discussion information-structuring model 17
2.3.1 Analysis of discussion information structure 17
2.3.2 Group consensus emergence 19
2.4 An example of consensus building using Premise-Warrant-Modality -Claim model 20
2.5 Summary 22
3 An Extended Argumentation Framework and its Extension Semantic 24
3.1 Introduction 24
3.2 Abstract Argumentation Framework 26
3.3 An extended argumentation framework 27
3.4 Evaluation of arguments 31
3.5 Case analysis 38
3.6 Conclusion and future work 41
4 An Argumentation-Based Interaction Model and its Algorithms in Multi-Agent System 42
4.1 Introduction 42
4.2 Framework of argumentation 43
4.3 Argumention algorithms 47
4.4 An example 49
4.5 Conclusions 52
5 Quantitative Deliberation Model and the Method of Consensus Building 54
5.1 Introduction 54
5.2 IBIS: Issue-Based Information System 55
5.3 Quantitative deliberation mode 56
5.4 Calculation of consensus values in QuDM 60
5.6 Conclusion 65
6 An Argumentation Model Based on Evidence Theory 66
6.1 Introduction 66
6.2 Argumentation framework and uncertain reasoning based on evidence theory 67
6.2.1 Basic argumentation framework 67
6.2.2 Uncertain reasoning based on DS evidence theory 68
6.3. Argumentation framework based on DS evidence theory 69
6.3.1 Frame of discernment of belief and opinion 69
6.3.2 The representation of argument based on DS evidence theory 70
6.3.3 The algorithm of opinion updating 70
6.4 Example 72
6.5 Summary 75
7 Multi-Documents Summarization based on TextRank and its Application in Online Argumentation Platform 76
7.1 Introduction 76
7.1.1 Background 76
7.1.2 Related works 78
7.1.3 The contributions 80
7.2 Multi-Document summarization based on TextRank algorithm 81
7.2.1Text pre-processing 82
7.2.2 Text clustering 85
7.2.3 Multi-Documents summarization 87
7.3 Application effect analysis 92
7.3.1 Experimental design 92
7.3.1.1 Participants and procedures 92
7.3.1.2 The design of test case 93
7.3.2 Experiment process 94
7.3.3 Effectiveness evaluation 99
7.4 Conclusion 101
8. Research on the Visualization in Group Deliberation Enviroment 103
8.1 Introduction 103
8.2 Visualized information 104
8.2.1 The visualization of the discussion information 105
8.2.2 The visualization of the state of consensus building 107
8.2.3 The visualization of the result of deliberation 107
8.3 The realization of visualization 108
8.3.1 Text visualization 108
8.3.2 Diagram visualization 108
8.4 The practical application and effect of GDE 109
8.4.1 The practical application of GDE 109
8.4.2 The analysis of the effect of the application 112
8.5 Conclusion 113
9. Personalized Group Recommendation Model based on Argumentation Topic 114
9.1 Introduction 114
9.2 Related work 116
9.3 Group recommendation model 117
9.3.1 The argumentation of topic determination and user grouping 118
9.3.2 Recommend model 119
9.5 Algorithm design 120
9.5.1 Content -based recommendation based on BP neural network. 120
9.5.2 Collaborative filtering algorithm based on topic 124
9.6 Application and evaluation 126
9.6.1 Experimental content 126
9.6.2 Experimental results and analysis. 126
9.7 Conclusion 128
10. Multi-Criteria Group Decision Making and Group Agreement Quotient Analysis based on the Delphi Method 130
10.1 Introduction 130
10.2 Multi-criteria decision making and group consistency analysis 131
10.2.1 Multi-resolution solution 131
10.2.2 The consistency of preference vector 132
10.2.3 The analsis of group agreement quotient 133
10.3 Research on decision-making process based on Delphi method 134
10.3.1 Delphi method 134
10.3.2 Decision-making process based on Delphi method 135
10.4 Case analysis 137
10.5 Result analysis 140
10.6 Conclusion 140
References 142
Readership
This book should be useful for students, scientists, engineers and professionals working in the areas of optoelectronic packaging, photonic devices, semiconductor technology, materials science, polymer science, electrical and electronics engineering. This book could be used for one semester course on adhesives for photonics packaging designed for both undergraduate and graduate engineering students.
