Heuristics in Analytics

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 xiAcknowledgments xixAbout the Authors xxiiiChapter 1: Introduction 1The Monty Hall Problem 5Evolving Analytics 8Summary 18Chapter 2: Unplanned Events, Heuristics, and the Randomness in Our World 23Heuristics Concepts 26The Butterfly Effect 30Random Walks 37Summary 44Chapter 3: The Heuristic Approach and Why We Use It 45Heuristics in Computing 47Heuristic Problem-Solving Methods 51Genetic Algorithms: A Formal Heuristic Approach 54Summary 67Chapter 4: The Analytical Approach 69Introduction to Analytical Modeling 71The Competitive-Intelligence Cycle 74Summary 97Chapter 5: Knowledge Applications That Solve Business Problems 101Customer Behavior Segmentation 102Collection Models 106Insolvency Prevention 113Fraud-Propensity Models 120Summary 127Chapter 6: The Graph Analysis Approach 129Introduction to Graph Analysis 130Summary 143Chapter 7: Graph Analysis Case Studies 147Case Study: Identifying Influencers in Telecommunications 149Case Study: Claim Validity Detection in Motor Insurance 162Case Study: Fraud Identification in Mobile Operations 178Summary 188Chapter 8: Text Analytics 191Text Analytics in the Competitive-Intelligence Cycle 193Linguistic Models 198Text-Mining Models 200Summary 207Bibliography 209Index 217