Найти книгу: "The Entail"

An introduction to greentailing and the five other biggest trends in the retail business In their newest book on retailing, authors Stern and Ander examine the revolutions occurring in the retail marketplace, with particular emphasis on the influential green trend in retailing, or Greentailing. Greentailing is capitalizing on the huge and growing demand for organic, sustainable and wellness-related products. As it evolves, greentailing will force both suppliers and retailers alike in every category to take notice. Leading edge greentailers like Whole Foods and Wal*Mart continue to grow and innovate at rates much faster than traditional competitors, and are forcing competitive responses. The authors explain how any retail store or manufacturer can implement these ideas and raise profits, using case studies from successful greentailers. In addition to greentailing, the book examines five other top retail trends: Demographic Shifts Provide Retail Opportunities Moving Up the Ladder—Growth of Experiential Retailing—How to Drive Sales and Profits Beyond Price Getting Outside the Box—New Ways to Reach the Consumer—The Growth of Non-Store Retailing Selling Services, Not Just products Brands Going Retail—The Battle for Control of the Customer Very much a follow up to their first book, Winning at Retail: Developing a Sustained Model for Retail Success, Greentailing and Other Revolutions in Retail addresses all the latest trends in the retail industry and presents unbeatable advice on quickly responding to changes in customer demographics and competition. Retail is all about the customer, and as customers and their tastes change, this one-of-a-kind resource shows retailers and manufacturers how to keep up and innovate.

In the last few years, a number of NLP researchers have developed and participated in the task of Recognizing Textual Entailment (RTE). This task encapsulates Natural Language Understanding capabilities within a very simple interface: recognizing when the meaning of a text snippet is contained in the meaning of a second piece of text. This simple abstraction of an exceedingly complex problem has broad appeal partly because it can be conceived also as a component in other NLP applications, from Machine Translation to Semantic Search to Information Extraction. It also avoids commitment to any specific meaning representation and reasoning framework, broadening its appeal within the research community. This level of abstraction also facilitates evaluation, a crucial component of any technological advancement program.
This book explains the RTE task formulation adopted by the NLP research community, and gives a clear overview of research in this area. It draws out commonalities in this research, detailing the intuitions behind dominant approaches and their theoretical underpinnings.
This book has been written with a wide audience in mind, but is intended to inform all readers about the state of the art in this fascinating field, to give a clear understanding of the principles underlying RTE research to date, and to highlight the short- and long-term research goals that will advance this technology.
Table of Contents: List of Figures / List of Tables / Preface / Acknowledgments / Textual Entailment / Architectures and Approaches / Alignment, Classification, and Learning / Case Studies / Knowledge Acquisition for Textual Entailment / Research Directions in RTE / Bibliography / Authors' Biographies