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Heuristics in analytics : a practical perspective of what influences our analytical world /
Employ heuristic adjustments for truly accurate analysis. Heuristics in Analytics presents an approach to analysis that accounts for the randomness of business and the competitive marketplace, creating a model that more accurately reflects the scenario at hand. With an emphasis on the importance of...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Hoboken, New Jersey :
Wiley,
[2014]
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
Tabla de Contenidos:
- Unplanned events, heuristics, and the randomness of the world
- The heuristic approach and why we use it
- The analytical approach
- Knowledge applications that solve business problems
- The graph analysis approach
- Graph analysis case studies
- Text analytics.
- Heuristics in Analytics: A Practical Perspective of What Influences Our Analytical World; Copyright; Contents; Preface; Acknowledgments; About the Authors; Chapter 1: Introduction; The Monty Hall Problem; Evolving Analytics; The Business Relevance of Analytics; The Role of Analytics in Innovation; Innovation in a Changing World; Summary; Chapter 2: Unplanned Events, Heuristics, and the Randomness in Our World; Heuristics Concepts; Heuristics in Operations; The Butterfly Effect; Random Walks; The Drunkard's Walk; Probability and Chance; Summary.
- Chapter 3: The Heuristic Approach and Why We Use It Heuristics in Computing; Heuristic Problem-Solving Methods; Genetic Algorithms: A Formal Heuristic Approach; Foundation of Genetic Algorithms; Initialization; Selection; Reproduction; Termination; Pseudo-Code Algorithm; Benefits of Genetic Algorithms; Influences in Competitive Industries; Genetic Algorithms Solving Business Problems; Summary; Chapter 4: The Analytical Approach; Introduction to Analytical Modeling; The Competitive-Intelligence Cycle; Data; Information; Knowledge; Intelligence; Experience; Summary.
- Chapter 5: Knowledge Applications That Solve Business Problems customer Behavior Segmentation; Collection Models; Insolvency Segmentation; Collection Notice Recovery; Anticipating Revenue from Collection Actions; Insolvency Prevention; Bad-Debt Classification; Avoiding Taxes; Fraud-Propensity Models; New Fraud Detection; Classifying Fraudulent Usage Behavior; Summary; Chapter 6: The Graph Analysis Approach; Introduction to Graph Analysis; Graphs Structures, Network Metrics, and Analyses Approaches; Network Metrics; Types of Subgraphs; Summary; Chapter 7: Graph Analysis Case Studies.
- Case Study: Identifying Influencers in Telecommunications background in Churn and Sales; Internal Networks; Customer Influence; Customer Influence and Business Event Correlation; Possible Business Applications and Final Figures in Churn and Sales; Case Study: Claim Validity Detection in Motor Insurance; Background in Insurance and Claims; Network Definition; Participant Networks; Group Analysis; Identifying Outliers; Final Figures in Claims; Visualizing for More Insight; Final Figures in Insurance Exaggeration; Case Study: Fraud Identification in Mobile Operations.
- Background in Telecommunications Fraud Social Networks and Fraud; Community Detection; Finding the Outliers within Communities; Rules and Thresholds for Community Outliers; Fraudsters Visualization; Final Figures in Fraud; Summary; Chapter 8: Text Analytics; Text Analytics in the Competitive-Intelligence Cycle; Information Revisited; Knowledge Revisited; Linguistic Models; Text-Mining Models; Intelligence Revisited; Experience Revisited; Summary; Bibliography; Index.