by ScottSpangler (Author), JeffreyKreulen (Author)
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.
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
Format: Paperback
Pages: 240
Edition: 1
Publisher: IBM Press
Published: 19 Jul 2007
ISBN 10: 0132339536
ISBN 13: 9780132339537
Book Overview: This is the first book to provide techniques and approaches for mining knowledge from unstructured business information and the business value of this analysis. Mining the Talk describes a fundamentally new approach to mining knowledge from unstructured business information. This unstructured information in free form text that the authors refer to as talk . It's simply the way humans have been communicating with each other for thousands of years, and it's the most prevalent kind of data to be found. Potentially, its also the most valuable, because hidden inside the talk is little bits and pieces of important information, which if aggregated and summarized could communicate actionable intelligence about how any business is running, how its customers and employees perceive it, what is going right and what is going wrong, and possibly solutions to the most pressing problems the business faces. These are examples of the gold that is waiting to be discovered if business can only Mine the Talk . The primary methodology employed centers on the creation of natural classifications (taxonomies) of the data objects. The book illustrates that the only way to insure the naturalness of taxonomies is through expert human intervention at every stage of the taxonomy generation and modeling process. After giving a high level overview the approach, the book dives into a series of real world examples showing how the mining techniques work in practice.
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.
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