Mining The Talk

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

The Business Year recently organized a series of panel discussions to discuss the investment opportunities in the sector and the importance of sustainability. This special debriefing includes a transcript of the entire event, as well as a series of other interviews, news, and analysis.

Though mining is an infamously masculine industry, women make up 20 percent of all production crews in Wyoming’s Powder River Basin—the largest coal-producing region in the United States. How do these women fit into a working culture supposedly hostile to females? This is what anthropologist Jessica Smith Rolston, herself a onetime mine worker and the daughter of a miner, set out to discover. Her answers, based on years of participant-observation in four mines and extensive interviews with miners, managers, engineers, and the families of mine employees, offer a rich and surprising view of the working “families” that miners construct. In this picture, gender roles are not nearly as straightforward—or as straitened—as stereotypes suggest. Gender is far from the primary concern of coworkers in crews. Far more important, Rolston finds, is protecting the safety of the entire crew and finding a way to treat each other well despite the stresses of their jobs. These miners share the burden of rotating shift work—continually switching between twelve-hour day and night shifts—which deprives them of the daily rhythms of a typical home, from morning breakfasts to bedtime stories. Rolston identifies the mine workers’ response to these shared challenges as a new sort of constructed kinship that both challenges and reproduces gender roles in their everyday working and family lives. Crews’ expectations for coworkers to treat one another like family and to adopt an “agricultural” work ethic tend to minimize gender differences. And yet, these differences remain tenacious in the equation of masculinity with technical expertise, and of femininity with household responsibilities. For Rolston, such lingering areas of inequality highlight the importance of structural constraints that flout a common impulse among men and women to neutralize the significance of gender, at home and in the workplace. At a time when the Appalachian region continues to dominate discussion of mining culture, this book provides a very different and unexpected view—of how miners live and work together, and of how their lives and work reconfigure ideas of gender and kinship.

In the years Bbetween the Meiji Restoration in 1868 and the beginning of the war mobilization boom in 1930, collieries in Europe and America embraced new technologies and had long since been excluded women from working underground. In Japan, however, mining women witnessed no significant changes in working practices over this period. The availability of the cheap and abundant labor of these women allowed the captains of the coal industry in Japan to avoid expensive investments in new machinery and sophisticated mining methods;, instead, they continued to intensely exploit workers and markets intensively, making substantial profits without the burdens of extensive mechanization. This unique book explores the lives of the thousands of women who labored underground in Japan’s coal mines in the years 1868 to 1930. It examines their working lives, their family lives, their aspirations, achievements and disappointments. Drawing heavily on interview material with the miners themselves, W. Donald Burton combines translations of their stories with features of Japanese society at the time and coal mining technology. In doing so, he presents a complex account of the women’s lives, as well as providing a keen insight intoon gender relations and the industrial and labor history of Japan. Coal Mining Women in Japan will be welcomed by students and scholars of Japanese history, gender studies and industrial history.

September 07-08, 2017 Paris, France Key Topics : Cloud computing, Forecasting from Big Data, Optimization and Big Data, New visualization techniques, Social network analysis, Search and data mining, Complexity and Algorithms, Open Data, ETL (Extract, Transform and Load), OLAP Technologies, Big Data Algorithm, Data Mining Analysis, Kernel Methods, Frequent Pattern Mining, Clustering, Data Privacy and Ethics, Big Data Technologies, Business Analytics, Data Mining Methods and Algorithms, Data Mining Tasks and Processes, Data Mining Applications in Science, Engineering, Healthcare and Medicine, Big Data Applications, Data Mining Tools and Software, Data Warehousing, Artificial Intelligence,