Part I: Concepts |
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1 Decision Making and Decision Support Systems |
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3 | |
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1.1 Decision Making and Decision Makers |
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3 | |
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1.2 Decision Problem Classification |
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4 | |
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1.3 Decision-Making Process |
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5 | |
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1.4 Decision Support Systems |
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8 | |
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1.5 Decision Support Techniques |
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11 | |
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1.5.2 Multiple Criteria Decision Making |
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12 | |
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1.5.4 Case-Based Reasoning |
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15 | |
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1.6 What's New in This Book? |
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1.6.1 The Decision Problems Oriented in This Book |
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1.6.2 New Models and Techniques for Ill-Structured Decision Problems |
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2.1 What Is Business Intelligence? |
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2.2 The Architecture of a Business Intelligence System |
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2.3 Analytics of Business Intelligence |
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2.4.1 SAS Business Intelligence |
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2.4.2 IBM Cognos Business Intelligence |
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26 | |
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2.4.3 SAP BusinessObjects Business Intelligence |
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3.1 The Concept of Cognition |
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33 | |
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3.4 Naturalistic Decision Making |
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34 | |
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37 | |
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4 Cognition in Business Decision Support Systems |
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39 | |
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4.1 Complex Nature of Business Decision Making |
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39 | |
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4.2 Cognition in Business Decision Making |
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41 | |
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4.3 Cognition Oriented Information Systems |
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4.3.1 Cognitive Decision Support Systems |
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42 | |
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4.3.2 Case-Based Reasoning Systems |
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44 | |
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4.3.3 Natural Language Interfaces to Database |
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4.3.3.1 Pattern-Matching NLIDB Systems |
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45 | |
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4.3.3.2 Syntax-Based NLIDB Systems |
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4.3.3.3 Semantic Grammar NLIDB Systems |
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48 | |
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Part II: Models |
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5 Cognition-Driven Decision Processes |
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53 | |
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5.1 Essentials of Cognition-Driven Decision Making |
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5.1.1 The Conceptual Framework of Cognitive Decision Support |
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5.1.2 Cognition-Driven Decision Processes |
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5.1.3 User Centered Decision Processes |
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5.2 The Cognition-Driven Decision Process Model |
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5.2.1 Situation Retrieval |
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5.2.1.1 Information Retrieval and Situation Retrieval |
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5.2.1.2 Information Need and Knowledge Need |
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62 | |
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5.2.1.3 Situation Retrieval Process |
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63 | |
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5.2.2 Generating Navigation Knowledge |
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68 | |
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5.2.3 Situation Presentation |
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69 | |
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5.2.4 Situation Awareness Updating |
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69 | |
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5.2.5 Decision Generation |
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70 | |
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71 | |
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Part III: Techniques |
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6 Domain Knowledge Representation and Processing |
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77 | |
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77 | |
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77 | |
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6.1.2 Property-Share Relationships |
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78 | |
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6.1.5 Role of the Ontology |
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6.2.1 Experience Representation |
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6.2.2 Experience Elicitation |
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6.2.3 Creating an Experience Base |
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6.2.6 Knowledge Retrieval |
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6.2.7 Generating Navigation Knowledge |
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7 Natural Language Processing for Situation Awareness |
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7.3 The Process of Situation Awareness Parsing |
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7.4 SA Plain Parsing: Instance Recognition |
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7.4.1 Numeric Meta Instances |
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7.4.2 Literal Meta Instances |
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7.4.3 Reference Properties |
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7.5 SA Semantic Parsing: Class Inferring |
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7.5.1 Class Trigger Construction |
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7.5.3 Reducing Uncertainties of SA Triples |
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112 | |
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7.6 Local Context Determination |
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7.6.1 Context Position Points |
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7.6.2 Context Coverage Points |
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7.6.3 Inverse Context Specificity Points |
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8 Data Warehouse Query Construction and Situation Presentation |
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8.1 Query Languages for Data Warehouses |
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8.1.1 Structured Query Language |
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8.1.2 Multidimensional Expressions |
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8.2 Framework of Query Construction and Situation Presentation |
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124 | |
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8.3 Determining Query Data Sources |
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126 | |
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8.4 Constructing SQL Queries |
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127 | |
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8.5 Constructing MDX Queries |
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131 | |
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8.6 Navigation-Knowledge-Guided Situation Presentation |
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136 | |
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8.7 Data Analysis and Situation Presentation |
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Part IV: Systems and Applications |
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9 A Cognition-Driven Decision Support System: FACETS |
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143 | |
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9.1 The Development Environment |
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143 | |
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9.2 The Architecture of FACETS |
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143 | |
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9.3.1 Data Warehouse System |
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9.3.2 Ontology Management |
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145 | |
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9.3.3 Experience Management |
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146 | |
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9.3.4 Situation Awareness Management |
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148 | |
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9.3.5 Situation Awareness Parsing |
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9.3.6 Situation Awareness Annotating |
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9.3.8 Situation Presentation |
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9.4 The Cognition-Driven Decision Process Based on FACETS |
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10 Evaluation of Algorithms and FACETS |
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157 | |
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10.1 Experiment Preparation |
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157 | |
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10.2 Experiment One: Algorithm Evaluation |
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10.2.2 Meta Instance Recognition |
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162 | |
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10.2.4 Local Context Determination |
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167 | |
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10.2.5 SA Triple Generation |
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169 | |
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10.2.6 Optimization Analysis |
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10.3 Experiment Two: System Evaluation |
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171 | |
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10.3.2 Query Construction Evaluation |
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172 | |
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11 Application Cases of FACETS |
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179 | |
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11.1 Application Case I: Business |
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179 | |
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11.1.1 Organization Background |
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179 | |
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11.1.3 The Experience Base |
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182 | |
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11.1.4 Decision Situation |
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183 | |
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210 | |
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11.2 Application Case II: Public Health |
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210 | |
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References |
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Abbreviations |
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233 | |
Index |
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