Mining the Talk: Unlocking the Business Value in Unstructured Information

Leverage Unstructured Data to Become More Competitive, Responsive, and Innovative

In Mining the Talk, two leading-edge IBM researchers introduce a revolutionary new approach to unlocking the business value hidden in virtually any form of unstructured data-from word processing documents to websites, emails to instant messages.

The authors review the business drivers that have made unstructured data so important-and explain why conventional methods for working with it are inadequate. Then, writing for business professionals-not just data mining specialists-they walk step-by-step through exploring your unstructured data, understanding it, and analyzing it effectively.

Next, you'll put IBM's techniques to work in five key areas: learning from your customer interactions; hearing the voices of customers when they're not talking to you; discovering the "collective consciousness" of your own organization; enhancing innovation; and spotting emerging trends. Whatever your organization, Mining the Talk offers you breakthrough opportunities to become more responsive, agile, and competitive.

• Identify your key information sources and what can be learned about them
• Discover the underlying structure inherent in your unstructured information
• Create flexible models that capture both domain knowledge and business objectives
• Create visual taxonomies: "pictures" of your data and its key interrelationships
• Combine structured and unstructured information to reveal hidden trends, patterns, and relationships
• Gain insights from "informal talk" by customers and employees
• Systematically leverage knowledge from technical literature, patents, and the Web
• Establish a sustainable process for creating continuing business value from unstructured data

Preface xv

Acknowledgements xx

Chapter 1: Introduction 1

Chapter 2: Mining Customer Interactions 21

Chapter 3: Mining the Voice of the Customer 71

Chapter 4: Mining the Voice of the Employee 93

Chapter 5: Mining to Improve Innovation 111

Chapter 6: Mining to See the Future 133

Chapter 7: Future Applications 163

Appendix: The IBM Unstructured Information Modeler Users Manual 171

W. Scott Spangler

IBM Research Division, Almaden Research Center, 650 Harry Road, San Jose, CA 95120 (email: spangles@almaden.ibm.com; ph. 408-927-2887)

Scott Spangler is a Senior Technical Staff Member who has been doing knowledge base and data mining research for the past 20 years-since 1996 at the IBM Research Lab and previously at the General Motors Technical Center, where he won the prestigious ＂Boss＂ Kettering award (1992) for technical achievement. He currently works in IBM Almaden Services Research, where he designs and implements new methodologies for data visualization and text mining. Mr. Spangler holds a B.S. degree in math from the Massachusetts Institute of Technology and an M.A. in computer science from the University of Texas.

Jeffrey T. Kreulen

IBM Research Division, Almaden Research Center, 650 Harry Road, San Jose, CA 95120 (email: kreulen@almaden.ibm.com)

Dr. Kreulen is Senior Manager of Services Oriented Technologies and Senior Technical Staff Member at the IBM Almaden Research Center. He holds a B.S. degree in applied mathematics (computer science) from Carnegie-Mellon University, and an M.S. degree in electrical engineering and a Ph.D. in computer engineering from Pennsylvania State University. Since joining IBM in 1992, he has worked on multiprocessor systems design and verification, operating systems, systems management, web-based service delivery, integrated text and data analysis, and the science of services.