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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,...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Upper Saddle River, N.J. :
IBM Press,
2007.
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 100 | 1 | |a Spangler, Scott. | |
| 245 | 1 | 0 | |a Mining the talk : |b unlocking the business value in unstructured information / |c Scott Spangler, Jeffrey Kreulen. |
| 260 | |a Upper Saddle River, N.J. : |b IBM Press, |c 2007. | ||
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| 504 | |a Includes bibliographical references and index. | ||
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a Ch. 1. Introduction -- A Short Story ... "The Contest" -- In the Beginning ... -- The Thesis -- The Business Context for Unstructured Information Mining -- Capturing Business Objectives and Domain Expertise -- A Common Analytical Methodology -- Applications for Mining the Talk -- The Transformation Process -- Summary -- Endnotes -- Ch. 2. Mining Customer Interactions -- A Brief Analogy to the Physical World -- Transactions Versus Interactions -- Business Drivers for Interactional Analysis -- Characteristics of Interactional Information -- What Can We Learn from Customer Interactions? -- The Mining the Talk Process for Customer Interactions -- Establishing a Continuous Process -- Customer Interactions Examples -- Summary -- Endnotes -- Ch. 3. Mining the Voice of the Customer -- Market Research vs. Mining the VoC -- Business Drivers for VoC Mining -- Characteristics of VoC Information -- What Can VoC Mining Teach Us? -- Stages of the VoC Mining Process -- Making VoC Mining an Ongoing Concern -- Making It Real: Detailed Examples -- Summary -- Endnotes -- Ch. 4. Mining the Voice of the Employee -- Business Drivers -- The Jam: Taking Corporate Communication to a New Level -- Stages of Mining the Jam -- Making Jams a Part of the Business -- Case Studies -- The Future of Jamming and Mining the Talk -- Summary -- Endnotes -- Ch. 5. Mining to Improve Innovation -- Business Drivers of Innovation Mining -- Characteristics of Innovation Information -- What Can Innovation Mining Teach Us? -- The Innovation Mining Process -- Making Innovation Mining an Ongoing Concern -- The Innovation Mining Process in Action: Finding the Most Relevant Patents in a Large Portfolio -- Research for a New Product: Mars Snackfood Division -- Summary -- Endnotes -- Ch. 6. Mining to See the Future -- How Can Unstructured Data Help Us to See the Future? -- Business Drivers of Future Mining -- Characteristics of Future-Oriented Data Sets -- Stages of Mining to See the Future -- Making Future Mining an Ongoing Concern -- Examples of Mining the Talk to See the Future -- Summary -- Endnotes -- Ch. 7. Future Applications -- Evaluating the Effectiveness of Talk on the Reader -- You Are What You Read -- Taxonomies as Knowledge Repositories -- Some Musings on a New Discipline in Mining the Talk -- Summary -- Final Words -- Endnote -- App. The IBM Unstructured Information Modeler Users Manual -- Introduction -- Installation -- Starting IBM Unstructured Information Modeler -- The IBM Unstructured Information Modeler Classification Process -- Interpreting IBM Unstructured Information Modeler Views -- IBM Unstructured Information Modeler Menus, Buttons, and Other Commands. | |
| 520 | |a 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 | ||
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Data mining. | |
| 650 | 0 | |a Soft computing. | |
| 650 | 0 | |a Business intelligence. | |
| 650 | 6 | |a Exploration de données (Informatique) | |
| 650 | 6 | |a Informatique douce. | |
| 650 | 7 | |a Data mining. |2 blmlsh | |
| 650 | 7 | |a Soft computing. |2 blmlsh | |
| 650 | 7 | |a Business intelligence. |2 blmlsh | |
| 650 | 7 | |a Business intelligence |2 fast | |
| 650 | 7 | |a Data mining |2 fast | |
| 650 | 7 | |a Soft computing |2 fast | |
| 700 | 1 | |a Kreulen, Jeffrey T. | |
| 776 | 0 | 8 | |i Print version: |a Spangler, Scott. |t Mining the talk. |d Upper Saddle River, N.J. : IBM Press, 2007 |z 9780132339537 |z 0132339536 |w (DLC) 2007018683 |w (OCoLC)128236671 |
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