All too often undergraduate readers can find themselves overwhelmed by foreign relations textbooks, the onslaught of names, events, and resultant policies and counterpolicies leaving them unable to form an appreciation, much less a working knowledge of, international relations. Worse yet, loose references to prominent scholars can leave them scratching their heads. It is with the student in mind that we are proud to present the second edition of our popular text, a concise narrative history that in straightforward language relates the long and complex history of the relationships between the United States and the nations of Latin America. Like its predecessor, this new editon of In the Eagle’s Shadowis ideal for use as a core text for courses in U.S-Latin American relations, as well as engaging supplementary reading for the U.S. or Latin American history surveys.

"This is the colorful and dramatic biography of two of America's most controversial entrepreneurs: Moses Louis Annenberg, 'the racing wire king, ' who built his fortune in racketeering, invested it in publishing, and lost much of it in the biggest tax evasion case in United States history; and his son, Walter, launcher of TV Guide and Seventeen magazines and former ambassador to Great Britain."--Jacket.

Tells the story of how America’s biggest companies began, operated, and prospered post-World War I This book takes the vantage point of people working within companies as they responded to constant change created by consumers and technology. It focuses on the entrepreneur, the firm, and the industry, by showing—from the inside—how businesses operated after 1920, while offering a good deal of Modern American social and cultural history. The case studies and contextual chapters provide an in-depth understanding of the evolution of American management over nearly 100 years. American Business Since 1920: How It Worked presents historical struggles with decision making and the trend towards relative decentralization through stories of extraordinarily capable entrepreneurs and the organizations they led. It covers: Henry Ford and his competitor Alfred Sloan at General Motors during the 1920s; Neil McElroy at Procter & Gamble in the 1930s; Ferdinand Eberstadt at the government’s Controlled Materials Plan during World War II; David Sarnoff at RCA in the 1950s and 1960s; and Ray Kroc and his McDonald’s franchises in the late twentieth century and early twenty-first; and more. It also delves into such modern success stories as Amazon.com, eBay, and Google. Provides deep analysis of some of the most successful companies of the 20th century Contains topical chapters covering titans of the 2000s Part of Wiley-Blackwell’s highly praised American History Series American Business Since 1920: How It Worked is designed for use in both basic and advanced courses in American history, at the undergraduate and graduate levels.

This book is aimed at providing an overview of several aspects of semantic role labeling. Chapter 1 begins with linguistic background on the definition of semantic roles and the controversies surrounding them. Chapter 2 describes how the theories have led to structured lexicons such as FrameNet, VerbNet and the PropBank Frame Files that in turn provide the basis for large scale semantic annotation of corpora. This data has facilitated the development of automatic semantic role labeling systems based on supervised machine learning techniques. Chapter 3 presents the general principles of applying both supervised and unsupervised machine learning to this task, with a description of the standard stages and feature choices, as well as giving details of several specific systems. Recent advances include the use of joint inference to take advantage of context sensitivities, and attempts to improve performance by closer integration of the syntactic parsing task with semantic role labeling. Chapter 3 also discusses the impact the granularity of the semantic roles has on system performance. Having outlined the basic approach with respect to English, Chapter 4 goes on to discuss applying the same techniques to other languages, using Chinese as the primary example. Although substantial training data is available for Chinese, this is not the case for many other languages, and techniques for projecting English role labels onto parallel corpora are also presented. Table of Contents: Preface / Semantic Roles / Available Lexical Resources / Machine Learning for Semantic Role Labeling / A Cross-Lingual Perspective / Summary