This book constitutes the thoroughly refereed post-proceedings of the 2006 Pacific Rim Knowledge Acquisition Workshop, PKAW 2006, held in Guilin, China in August 2006 as part of 9th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2006.
The 21 revised full papers and 6 revised short papers presented together with 4 invited talks were carefully reviewed and selected from 81 submissions. The papers are organized in topical sections on ontology and knowledge acquisition, algorithm approaches to knowledge acquisition, incremental knowledge acquisition and RDR, knowledge acquisition and applications, as well as machine learning and data mining.
Author(s): Achim Hoffmann, Byeong-ho Kang, Debbie Richards, Shusaku Tsumoto
Series: Lecture Notes in Artificial Intelligence 4303
Edition: 1
Publisher: Springer
Year: 2006
Language: English
Pages: 267
Front matter......Page 1
Introduction......Page 10
Image Segmentation......Page 11
MPEG-7......Page 12
Overview of the Methodology......Page 13
Image Processing and Low Level Features Extraction......Page 14
Qualitative Spatial Information Extraction......Page 15
Example......Page 16
Discussion and Conclusions......Page 19
References......Page 20
Introduction......Page 22
Automatic Generation of Ontologies......Page 24
Applications of Adhoc and Personal Ontologies......Page 28
Discussion and Conclusion......Page 30
References......Page 31
Introduction......Page 34
Business Process Modeling with BPMN......Page 35
Goal-Oriented Requirements Engineering with KAOS......Page 36
Using Model Annotations to Verify Goal Satisfaction......Page 38
Effect Annotations......Page 39
Trajectory Decomposition......Page 40
Goal Satisfaction and Cumulative Effect Assessment......Page 41
Current Business Context and Process......Page 42
Applying GoalBPM......Page 43
Changes to the Goal Model......Page 45
References......Page 47
Introduction......Page 49
Syntactic-Semantic Categories and Rules......Page 50
Morphological Analysis of Numeral Strings......Page 52
Classification Based on Word Trigrams......Page 53
Experimental Results......Page 56
References......Page 58
Introduction......Page 60
RFID Technology and Its Application to Libraries......Page 62
In-the-Library Marketing with RFID......Page 65
Data Collection......Page 66
Analysis......Page 67
Improvement......Page 69
Security Issue......Page 70
Concluding Remarks......Page 71
References......Page 72
Introduction......Page 73
Chunkingless Graph-Based Induction(Cl-GBI)......Page 74
Patterns Used as Constraints......Page 75
Design of Constrained Search......Page 77
Experimental Settings......Page 79
Experimental Results......Page 81
Conclusion......Page 82
Introduction......Page 84
Rule Evaluation Support with Rule Evaluation Model Based on Objective Indices......Page 85
Performance Comparisons of Learning Algorithms for Rule Model Construction......Page 86
A Case Study on the Meningitis Datamining Result......Page 87
A Case Study on the Chronic Hepatitis Datamining Results......Page 90
An Experiment on Artificial Evaluation Labels......Page 93
Conclusion......Page 94
Introduction......Page 98
ROC Analysis......Page 99
EMAUC Algorithm......Page 100
Experimental Results......Page 103
Conclusion......Page 105
Introduction......Page 108
The ACA Knowledge Intellectual Structure Methodology......Page 109
The Intellectual Structure of Knowledge Management......Page 110
Factor Analysis......Page 111
Pathfinder Network......Page 113
Conclusion......Page 114
References......Page 115
Introduction......Page 117
The 5Cs System......Page 118
Tracking Case-RuleNode Associations......Page 119
Results of the FastFIX Software Trial......Page 121
Solution Effectiveness......Page 122
Case Drop-Throughs......Page 123
Individual KA Curves......Page 125
Conclusions......Page 127
References......Page 128
Introduction......Page 129
Database......Page 130
Multiple Classification Ripple Down Rules......Page 131
Knowledge Acquisition......Page 132
Growth of Knowledge Base......Page 133
Correct Conclusions Found......Page 134
Percentage of Classifications Missed......Page 135
Maintainability and Usability......Page 136
Structure of the Knowledge Base......Page 137
Conclusions......Page 138
Standardisation......Page 139
References......Page 140
Introduction......Page 141
Conceptual Scaling......Page 143
Formal Framework of Conceptual Scaling......Page 144
Conceptual Scaling for Ontological Attributes......Page 145
Conceptual Scaling for Grouping Keywords......Page 147
Implementation......Page 149
Discussion and Conclusion......Page 150
References......Page 151
Introduction......Page 153
Overview for Video Analysis......Page 154
Domain Knowledge Infrastructure......Page 156
Video Content Representation Through Domain-Specific Ontology......Page 158
Analytical Results for Video Content Retrieval......Page 161
References......Page 163
Introduction......Page 165
Electronic Healthcare Records......Page 166
CEN......Page 167
OpenEHR......Page 168
Ontologies for Integration and Interoperability......Page 169
The Ontological Infrastructure......Page 170
From Information Models to Ontological Representation......Page 171
Conclusions......Page 174
References......Page 175
Introduction......Page 177
Reinforcement Learning......Page 178
Test House......Page 179
System Embodiment......Page 180
Result of Experiment......Page 181
References......Page 184
Introduction......Page 186
Dissimilarity-Based Classification......Page 189
Spatially Weighted Gray-Level Hausdorff Distance......Page 190
Experimental Results......Page 192
Conclusions......Page 194
Introduction......Page 196
Preliminaries......Page 197
Main Notion......Page 198
Main Result and Verification......Page 199
Neural Networks and Finite State Automata......Page 201
Main Algorithm......Page 202
Open Questions......Page 204
Introduction......Page 208
Common Vectors Using k-Clustering Method......Page 209
$k$-Clustering Method......Page 210
Finding Total Common Vector......Page 211
Experiments and Results......Page 212
Conclusion......Page 214
Introduction......Page 216
Background Knowledge and Our Approach......Page 217
Experimental Results and Evaluation......Page 221
Conclusion......Page 223
References......Page 224
Introduction......Page 225
Lexical Similarities......Page 226
An Iterative Approach to Learn Conceptual Graphs......Page 227
Term to Concept Mapping Using the Ontology......Page 228
Related Work......Page 229
Conclusion and Future Work......Page 230
Introduction......Page 232
Ontology Formalization and Integration......Page 233
References......Page 237
Introduction......Page 239
Rule Graphs and State-Independent Activation Sets......Page 240
Calculate State-Independent Activation Sets and Use Them in Relax-Plan......Page 242
Experiments with FF-DP......Page 244
Conclusion......Page 245
References......Page 246
The Proposed System......Page 247
Implementation and Results......Page 251
References......Page 252
Introduction......Page 253
Information Retrieval Systems......Page 254
Using Problem Specific Knowledge to Enhance Information Retrieval......Page 255
Experimental Result......Page 258
Discussion and Conclusions......Page 259
References......Page 260
The Approach......Page 261
Results and Findings......Page 263
Conclusion and Future Work......Page 265
References......Page 266
Back matter......Page 267
