v
TABLE OF CONTENTS
Abstract
iii Table of Contents
v
Acknowledgements
ix
List of Publications
xii
Contribution of the Thesis
xvii
Index of Figures
xx
Index of Tables
xxii
Index of Abbreviations and Acronyms
xxiii
CHAPTER 1: INTRODUCTION
1
1.1 Overview 1
1.2 Ethical Considerations 6
1.3 Delimitations of the Thesis 7
1.4 Organisation of the Thesis 8
CHAPTER 2: BACKGROUND 11
2.1 Introduction
11 2.2
Artificial Intelligence AI 12
2.3 Turing Test and Loebner Prize
13 2.4
State-of-the-arts Conversation Agents System 17
2.4.1 Classical Conversation Agents System
21 2.4.1.1
ELIZA 21
2.4.1.2 PARRY
23 2.4.2
Conversation Agents in the Loebner Prize 25
2.4.2.1 ALICE
26 2.4.2.2
Jaberwacky 33
2.4.3 Commercial Conversation Agents System
35 2.4.3.1 Anna
36 2.4.3.2 Spleak
37 2.4.4
Tricks or AI 38
2.5 New Challenges
41 2.5.1
Natural Language Understanding 41
2.5.2 World Knowledge
42 2.5.3
Human-machine Interface 43
2.6 Summary
43
vi
CHAPTER 3: CONVERSATION AGENTS FRAMEWORK DESIGN 46
3.1 Introduction 46
3.2 Conversation Agents Framework 46
3.2.1 Reusability 47
3.2.2 Modularity 48
3.2.3 Extensibility 48
3.2.4 Scalability 48
3.3 Conversation Agents’ Features 49
3.3.1 Modules Integration 49
3.3.2 Domain Independent 49
3.3.3 Cross-Platform 50
3.4 N-tiered Architecture 51
3.5 AINI ‘s Conversation Agents Architecture 52
3.5.1 AINI’s Modified N-tiered Architecture 53
3.5.1.1 Channel Service Tier 55
3.5.1.2 Domain Service Tier 55
3.5.2 Agent Body Client Tier 57
3.5.2.1 WebChat 58
3.5.2.2 MobileChat 60
3.5.2.3 MSNChat 62
3.5.2.4 Proxy Conversation Example 1 66
3.5.3 Agent Knowledge Data Server Tier 69
3.5.3.1 Domain Knowledge Matrix Model DKMM 70
3.5.3.2 Open-Domain Knowledge Bases 72
3.5.3.3 Domain-Specific Knowledge Bases 76
3.5.3.4 Stimulus-Response Categories in AINI’s Knowledge bases 76
3.5.3.5 Proxy Conversation Example 2 77
3.5.4 Agent Brain Application Server Tier 79
3.5.4.1 Multilevel Natural Language Query 80
3.5.4.2 Spell Checker 81
3.5.4.3 Natural Language Understanding and Reasoning NLUR 83
3.5.4.4 Frequently Asked Questions Chat FAQChat 86
3.5.4.5 Index Search 87
3.5.4.6 Pattern Matching Case-based Reasoning PMCBR 87
3.5.4.7 Supervised Learning Approach by Domain Expert 90
3.5.4.8 Proxy Conversation Example 3 92
3.6 Adaptability of the AINI’s Framework into other Domain Application 95 3.7 AINI Compares with others Conversation Agents
98 3.7.1 Multilevel Natural Language Query
98 3.7.2 Spelling Correction
98 3.7.3 Implementation
99 3.7.4 Supervise Learning
101 3.7.5 Dynamic Responses
102 3.8 Summary
102 CHAPTER 4 AN ASSESSMENT OF THE TRUSTWORTHINESS OF
104 KNOWLEDGE BASES FOR CONVERSATION AGENTS
4.1 Introduction
104 4.2
Trust and Methodology 106
4.3 Website as the Object of Trust
112
vii 4.4
Trust Model 112
4.5 Web Knowledge Trust Model WKTM
113 4.5.1
Selecting Domain-Specific Web Knowledge 115
4.5.2 Seeding
116 4.5.3
Building a Corpus 118
4.5.4 Evaluating a Corpus
120 4.5.4.1
Log Likelihood Ratio 121
4.5.4.2 PageRank
123 4.5.4.3
Web Credibility 126
4.5.5 Trustworthiness Websites
130 4.6 Automated Knowledge Extraction Agent AKEA
132 4.6.1 Crawler
132 4.6.2 Wrapper
133 4.6.3 Text Categoriser
134 4.6.4 Syntactic Preprocessor
134 4.6.5 Semantic Parser
134 4.6.6 Semantic Interpreter
135 4.6.7 Query Engine
135 4.7 Summary
137
CHAPTER 5: AN EVALUATION OF THE CONVERSATION AGENTS 139 FRAMEWORK
