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

Mining the Talk: Unlocking the Business Value in Unstructured Information

Business & Money

Spangler, Scott

Management & Leadership

Ibm Press

Accelerating Discovery: Mining Unstructured Information for Hypothesis Generation (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)

Unstructured Mining Approaches to Solve Complex Scientific Problems\nAs the volume of scientific data and literature increases exponentially, scientists need more powerful tools and methods to process and synthesize information and to formulate new hypotheses that are most likely to be both true and important. Accelerating Discovery: Mining Unstructured Information for Hypothesis Generation describes a novel approach to scientific research that uses unstructured data analysis as a generative tool for new hypotheses.\nThe author develops a systematic process for leveraging heterogeneous structured and unstructured data sources, data mining, and computational architectures to make the discovery process faster and more effective. This process accelerates human creativity by allowing scientists and inventors to more readily analyze and comprehend the space of possibilities, compare alternatives, and discover entirely new approaches.\nEncompassing systematic and practical perspectives, the book provides the necessary motivation and strategies as well as a heterogeneous set of comprehensive, illustrative examples. It reveals the importance of heterogeneous data analytics in aiding scientific discoveries and furthers data science as a discipline.

Economics

Chapman and Hall/CRC

Unstructured Mining Approaches to Solve Complex Scientific Problems As the volume of scientific data and literature increases exponentially, scientists need more powerful tools and methods to process and synthesize information and to formulate new hypotheses that are most likely to be both true and important. Accelerating Discovery: Mining Unstructured Information for Hypothesis Generation describes a novel approach to scientific research that uses unstructured data analysis as a generative tool for new hypotheses. The author develops a systematic process for leveraging heterogeneous structured and unstructured data sources, data mining, and computational architectures to make the discovery process faster and more effective. This process accelerates human creativity by allowing scientists and inventors to more readily analyze and comprehend the space of possibilities, compare alternatives, and discover entirely new approaches. Encompassing systematic and practical perspectives, the book provides the necessary motivation and strategies as well as a heterogeneous set of comprehensive, illustrative examples. It reveals the importance of heterogeneous data analytics in aiding scientific discoveries and furthers data science as a discipline.

See the best price to sell, buy, or rent books by Spangler, Scott. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Books by Spangler, Scott

See the best price to sell, buy, or rent books by Spangler, Scott. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Mining the Talk: Unlocking the Business Value in Unstructured Information

Accelerating Discovery: Mining Unstructured Information for Hypothesis Generation (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)

Accelerating Discovery: Mining Unstructured Information for Hypothesis Generation (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)