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CARLOS ANDRE REIS PINHEIRO is Visiting Professor at KU Leuven, Belgium. He headed the Analytical Lab at Oi in Brazil, one of the largest telecommunications companies in Latin America. Pinheiro has conducted Postdoctoral Research at Katholieke Universiteit Leuven, Belgium, Université de Savoie, France and Dublin City University, Ireland. He holds a PhD in Engineering from Federal University of Rio de Janeiro, Brazil. He worked at Brazil Telecom for almost ten years and also accomplished postdoctoral research at IMPA, Brazil, one of the most prestigious mathematical institutions in the world. He has published several papers in international journals and conferences and has four books (all in Portuguese) that focus on the internet, database, web warehousing, and analytical intelligence. He is the author of Social Network Analysis in Telecommunications, published by Wiley.
FIONA McNEILL has applied analytics to business problems since she began her career in 1992 and has consistently helped companies benefit from strategic use of data and analytics. Throughout her career, she has been affiliated with data and technology companies, from information and survey providers, IBM Global Services and for over fifteen years, at SAS. McNeill has published in academic journals, conducted education seminars and presented at both academic and industry conferences over the course of her career. She holds an M.A. in Quantitative Behavioral Geography from McMaster University, and graduated cum laude with a B.Sc. in Bio-Physical Systems, University of Toronto.
Preface
Acknowledgments
About the Authors
Chapter 1: Introduction
The Monty Hall Problem
Evolving Analytics
Summary
What Comes Next
Chapter 2: Unplanned Events, Heuristics and the Randomness in Our World
Heuristics Concepts
The Butterfly Effect
Random Walks
Chapter 3: The Heuristic Approach and Why We Use It
Heuristics in computing
Heuristic Problem solving Methods
Genetic Algorithms: a Formal Heuristic Approach
Chapter 4: The Analytical Approach
Introduction to Analytical Modeling
The Competitive Intelligence Cycle
Chapter 5: Knowledge Applications That Solve Business Problems
Customer Behavioral Segmentation
Collection Models
Insolvency Prevention
Fraud Propensity Models
Chapter 6: The Graph Analysis Approach
Introduction to Graph Analysis
Chapter 7: Graph Analysis Case Studies
Case Study: Identifying Influencers
Case Study: Claim Validity Detection
Case Study: Fraud Identification
Chapter 8: Text Analytics
Text Analytics in the Competitive Intelligence Cycle
Linguistic Models
Text Mining Models
Recommended Reading
Bibliography
Index
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