โ Scribed by Ras, Zbigniew W.; Dardzinska, Agnieszka
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Foundations of Computational Intelligence Volume 2: Approximation Reasoning: Theoretical Foundations and Applications Human reasoning usually is very approximate and involves various types of - certainties. Approximate reasoning is the computational modelling of any part of the process used by humans to reason about natural phenomena or to solve real world problems. The scope of this book includes fuzzy sets, Dempster-Shafer theory, multi-valued logic, probability, random sets, and rough set, near set and hybrid intelligent systems. Besides research articles and expository papers on t- ory and algorithms of approximation reasoning, papers on numerical experiments and real world applications were also encouraged. This Volume comprises of 12 chapters including an overview chapter providing an up-to-date and state-of-the research on the applications of Computational Intelligence techniques for - proximation reasoning. The Volume is divided into 2 parts: Part-I: Approximate Reasoning Theoretical Foundations Part-II: Approximate Reasoning Success Stories and Real World Applications Part I on Approximate Reasoning Theoretical Foundations contains four ch- ters that describe several approaches of fuzzy and Para consistent annotated logic approximation reasoning. In Chapter 1, Fuzzy Sets, Near Sets, and Rough Sets for Your Computational Intelligence Toolbox by Peters considers how a user might utilize fuzzy sets, near sets, and rough sets, taken separately or taken together in hybridizations as part of a computational intelligence toolbox. In multi-criteria decision making, it is necessary to aggregate (combine) utility values corresponding to several criteria (parameters)."
Title Page......Page 2
Preface......Page 6
Contents......Page 11
Part I Information Retrieval and Web Intelligence......Page 14
Introduction......Page 15
Related Work......Page 19
The Algorithm......Page 21
Analysis......Page 26
Implementation and Experiments......Page 28
{\it Simple Workloads}......Page 29
{\it Complex Workloads}......Page 30
Conclusions......Page 34
References......Page 35
Introduction......Page 37
Hyperlinks as Semantic Markup......Page 40
The Unified Web model......Page 41
{\it Wordsets and Wordset Pairs}......Page 43
{\it Formal Description of HQL}......Page 44
Implementation and Results......Page 50
{\it Qualitative Analysis}......Page 52
{\it Quantitative Analysis}......Page 55
Related Research......Page 56
Conclusion and Future Work......Page 58
References......Page 59
Introduction......Page 61
On Some Related Works......Page 63
{\it Fuzzification of the Lacroix and Lavency Approach}......Page 67
Queries with Preferences and Bipolar Queries......Page 72
Concluding Remarks......Page 76
References......Page 77
Introduction......Page 79
Representing Background Knowledge โ Ontology......Page 80
{\it An Algebraic Approach to Ontologies}......Page 81
{\it Modelling Ontologies}......Page 82
Referencing the Background Knowledge โ Providing Descriptions......Page 83
{\it Instantiated Ontology}......Page 87
{\it Weighted Descriptors}......Page 88
Data Summarization through Background Knowledge......Page 89
{\it Connectivity Clustering}......Page 90
{\it Similarity Clustering}......Page 93
{\it A Probability-Based Approach}......Page 96
Concluding Remarks......Page 97
References......Page 98
Introduction......Page 100
{\it Multilevel View and Multiview Understanding}......Page 101
{\it Structured Thinking}......Page 102
{\it Structured Problem Solving}......Page 103
{\it Structured Information Processing}......Page 104
Web Intelligence (WI)......Page 105
{\it The Relevance of Granular Computing}......Page 106
{\it Multiview Understanding of the Web}......Page 107
{\it Web-Based Information Retrieval Support Systems}......Page 108
References......Page 111
Part II Knowledge Discovery......Page 114
Introduction......Page 115
Scientific Visualization......Page 117
{\it Scientific Visualization as More Than Projection}......Page 118
{\it Scientific Visualization as Projection Plus Visualization}......Page 119
Scientific Visualizing Applied to Performance Data Visualization......Page 120
{\it Traditional Classifier Evaluation}......Page 121
{\it Visualization-Based Evaluation}......Page 122
{\it Methodology}......Page 124
{\it Implementation}......Page 125
{\it MCST: A Distance Preserving Projection Approach}......Page 127
{\it Experiments on Several Binary Domains}......Page 128
{\it Experiments on Single Multiclass Domains}......Page 133
{\it Experiments on Domain Difficulties}......Page 135
Concluding Remarks......Page 138
References......Page 139
Introduction......Page 140
{\it Basic Notation}......Page 142
{\it Perspectives of Rule Induction and Evaluation}......Page 143
{\it Induction of Minimal Sets of Rules}......Page 145
{\it Induction of Non-minimal Sets of Rules}......Page 146
EXPLORE Algorithm......Page 148
{\it Presentation of the Algorithm}......Page 149
{\it Example: Using EXPLORE for Technical Diagnostics}......Page 151
{\it Other Experience with EXPLORE}......Page 152
Handling Imbalanced Data......Page 153
Replacing a Set of Rules for the Minority Class......Page 156
Experimental Evaluation......Page 157
Conclusions......Page 160
References......Page 161
Introduction......Page 164
Sequence Concepts......Page 165
{\it Horizontal Sequence Organizations}......Page 168
{\it Vertical Sequence Organizations}......Page 170
{\it Event Sequences}......Page 171
Missing Values......Page 173
{\it Converting between State Sequence Formats}......Page 174
{\it Converting between Event Sequence Formats}......Page 176
{\it Conversion from State to Event Sequences}......Page 177
{\it Conversion from Event to State Sequences}......Page 179
Conclusion......Page 182
References......Page 183
Introduction......Page 185
{\it Analyzed Data}......Page 187
{\it Association Rules and 4ft-Miner Procedure}......Page 188
{\it Defining the Set of Relevant Boolean Attributes}......Page 190
{\it Additional GUHA Procedures}......Page 191
Logical Calculi of Association Rules......Page 192
Domain Knowledge......Page 193
{\it Principles โ Patterns of Analytical Questions}......Page 195
{\it Initial Set Up of 4ft-Miner Parameters}......Page 197
{\it Modification of Parameters for the 4ft-Miner Procedure}......Page 198
{\it Atomic Consequences}......Page 199
{\it Logical Consequences of Atomic Consequences}......Page 201
Logical Calculi for Analytical Questions and Reports......Page 203
References......Page 206
Part III Information Integration and Data Security......Page 208
A Study on Recent Trends on Integration of Security Mechanisms......Page 209
Introduction......Page 210
Genesis of Conflicts......Page 211
{\it Composition of Socio-technical Security Solutions}......Page 212
{\it Composition of Security Solutions Sharing Technical Context}......Page 215
{\it Composition of Security Solutions Sharing Technical and Functional Context}......Page 220
Smart Items Case Study......Page 222
Conclusion and Future Work......Page 225
References......Page 226
Introduction......Page 231
Privacy Agreement Model......Page 234
Overview of the Monitoring Framework......Page 236
{\it Monitoring Units for Privacy}......Page 237
{\it Privacy Misuses}......Page 238
Monitoring Private Data Use Flow......Page 239
Architecture and Implementation......Page 243
Related Work......Page 250
Conclusion......Page 251
References......Page 252
Introduction......Page 254
Articulation Management and Ontology Algebra......Page 257
{\it Document Querying Based on Articulation and Algebra}......Page 260
{\it NETMARK System Design}......Page 263
{\it Data Storage}......Page 264
{\it Efficient Query Processing}......Page 267
Performance......Page 268
{\it Performance Results}......Page 269
Application, Case-Studies......Page 271
System Interface and Availability......Page 274
Related Work......Page 275
Conclusions and Current Work......Page 276
References......Page 277
Part IV Intelligent Agents......Page 280
Introduction......Page 281
{\it Principles of Pervasive Systems}......Page 283
{\it Projects of Pervasive System}......Page 286
Related Database Research......Page 288
{\it Data Streams}......Page 289
{\it Data and Services Integration}......Page 290
Enabling Technologies......Page 291
SoCQ: A Comprehensive PEMS......Page 292
{\it Example Scenario}......Page 293
{\it Modeling of Pervasive Environments}......Page 295
{\it Implementation of PEMS}......Page 297
References......Page 299
Introduction......Page 303
{\it Swarm Robots}......Page 304
{\it Expressing Probabilistic Knowledge}......Page 305
{\it Inferencing the Joint Probability Distribution}......Page 306
Toward a Novel Design of Swarm Robots......Page 307
{\it Collision Avoidance Problem and Our Swarm Robot}......Page 309
{\it Prediction Based on a Dynamic Bayesian Network}......Page 310
{\it Measurement of Basic Statistics}......Page 312
References......Page 313
Introduction......Page 315
{\it Standard Possibilistic Logic}......Page 316
{\it Default Reasoning, Causality and Belief Revision}......Page 319
{\it Fusion}......Page 320
Further Representation Issues: Bipolarity and Agentivity......Page 321
{\it Bipolar Possibilistic Representations}......Page 322
{\it Multiple Agent Possibilistic Logic}......Page 323
Representation of Preferences......Page 326
Handling Uncertainty in Possibilistic Databases......Page 328
References......Page 330
Part V Data Management in Medical Domain......Page 335
Introduction......Page 336
The STULONG Study......Page 337
The KEX Algorithm......Page 340
KEX Applied to the STULONG Study......Page 343
Rule Base Modifications......Page 346
{\it Basic Principles of NEST}......Page 347
Comparison with Atherosclerosis Risk Calculators......Page 350
Conclusions......Page 352
References......Page 353
{\it Introduction}......Page 354
Formal Representation of Imprecision......Page 355
An Overview of Approaches to the Definition of Imprecision......Page 356
Interpretation of Imprecision......Page 357
Medical Data Definition......Page 358
General Data Definition......Page 359
Medical Data Characteristics......Page 360
Medical Data and the Data-Information-Knowledge Spectrum......Page 362
{\it Imprecision in Medical Data}......Page 364
Semiotic Approach......Page 365
Fuzzy Logic Approach......Page 369
{\it Conclusions and Future Work}......Page 370
References......Page 371
Introduction......Page 373
{\it Aspect-Level Performance: Promoting Diversity in the Top Hits}......Page 374
{\it Biclustering of Passages}......Page 375
{\it Cosine Similarity Textual Clustering}......Page 376
{\it Query Term Expansion}......Page 377
{\it Ontology-Based Data Integration in Bioinformatics}......Page 378
{\it Ontological Term Extraction from Passages}......Page 379
{\it HIERDENC: Density-Based Clustering for Reranking Passages}......Page 383
Evaluation: Results and Discussions......Page 385
{\it Aspect-Level Retrieval on TREC 2007 Genomics Track}......Page 386
{\it Conclusions}......Page 392
{\it Future Work}......Page 393
References......Page 394
Author Index......Page 396
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