Written from a computer science perspective by three leading experts in the field, it gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Although originally designed as the primary text for a graduate or advanced undergraduate course in information retrieval, the book will also create a buzz for researchers and professionals alike.

    Writing is hard work and can be difficult to wedge into a frenetic academic schedule.This revised and updated edition of Paul Silvia's popular guide provides practical, light-hearted advice to help academics overcome common barriers and become productive writers. Silvia's expert tips have been updated to apply to a wide variety of disciplines, and this edition has a new chapter devoted to grant and fellowship writing.

    It draws our attention away from the bright shiny objects of the new colonialism through elucidating the social, material and political dimensions of Artificial Intelligence.”—Geoffrey C. Bowker, University of California, Irvine What happens when artificial intelligence saturates political life and depletes the planet? How is AI shaping our understanding of ourselves and our societies? In this book Kate Crawford reveals how this planetary network is fueling a shift toward undemocratic governance and increased racial, gender, and economic inequality. Drawing on more than a decade of research, award‑winning science, and technology, Crawford reveals how AI is a technology of extraction: from the energy and minerals needed to build and sustain its infrastructure, to the exploited workers behind “automated” services, to the data AI collects from us.    Rather than taking a narrow focus on code and algorithms, Crawford offers us a political and a material perspective on what it takes to make artificial intelligence and where it goes wrong. While technical systems present a veneer of objectivity, they are always systems of power. This is an urgent account of what is at stake as technology companies use artificial intelligence to reshape the world.

    Infrastructure engineers use a software version of this “chaos monkey” to test online services’ robustness—their ability to survive random failure and correct mistakes before they actually occur. Tech entrepreneurs are society’s chaos monkeys, disruptors testing and transforming every aspect of our lives, from transportation (Uber) and lodging (AirBnB) to television (Netflix) and dating (Tinder). One of Silicon Valley’s most audacious chaos monkeys is Antonio García Martínez.After stints on Wall Street and as CEO of his own startup, García Martínez joined Facebook’s nascent advertising team, turning its users’ data into profit for COO Sheryl Sandberg and chairman and CEO Mark “Zuck” Zuckerberg. Forced out in the wake of an internal product war over the future of the company’s monetization strategy, García Martínez eventually landed at rival Twitter. He also fathered two children with a woman he barely knew, committed lewd acts and brewed illegal beer on the Facebook campus (accidentally flooding Zuckerberg's desk), lived on a sailboat, raced sport cars on the 101, and enthusiastically pursued the life of an overpaid Silicon Valley wastrel.Now, this gleeful contrarian unravels the chaotic evolution of social media and online marketing and reveals how it is invading our lives and shaping our future. Weighing in on everything from startups and credit derivatives to Big Brother and data tracking, social media monetization and digital “privacy,” García Martínez shares his scathing observations and outrageous antics, taking us on a humorous, subversive tour of the fascinatingly insular tech industry. Chaos Monkeys lays bare the hijinks, trade secrets, and power plays of the visionaries, grunts, sociopaths, opportunists, accidental tourists, and money cowboys who are revolutionizing our world. The question is, will we survive?

    When it was originally published in 1974, E. Evans-Pritchard of the Times Literary Supplement noted that this classic study of anthropological economics "is rich in factual evidence and in ideas, so rich that a brief review cannot do it justice; only another book could do that."

    Used in university courses and professional seminars all over the world, the text has proven its ability to open minds and sharpen thinking.Originally published in 1975 and reprinted more than twenty times over a quarter century -- and now available for the first time from Dorset House Publishing -- the text uses clear writing and basic algebraic principles to explore new approaches to projects, products, organizations, and virtually any kind of system.Scientists, engineers, organization leaders, managers, doctors, students, and thinkers of all disciplines can use this book to dispel the mental fog that clouds problem-solving. As author Gerald M. Weinberg writes in the new preface to the Silver Anniversary Edition, "I haven’t changed my conviction that most people don’t think nearly as well as they could had they been taught some principles of thinking.”Now an award-winning author of nearly forty books spanning the entire software development life cycle, Weinberg had already acquired extensive experience as a programmer, manager, university professor, and consultant when this book was originally published.With helpful illustrations, numerous end-of-chapter exercises, and an appendix on a mathematical notation used in problem-solving, An Introduction to General Systems Thinking may be your most powerful tool in working with problems, systems, and solutions.

    Nations worry about the learning of their citizens, companies about the learning of their workers, schools about the learning of their students. But it is not always easy to think about how to foster learning in innovative ways. This book presents a framework for doing that, with a social theory of learning that is ground-breaking yet accessible, with profound implications not only for research, but also for all those who have to foster learning as part of their responsibilites at work, at home, at school.

    Wolfram lets the world see his work in A New Kind of Science, a gorgeous, 1,280-page tome more than a decade in the making. With patience, insight, and self-confidence to spare, Wolfram outlines a fundamental new way of modeling complex systems. On the frontier of complexity science since he was a boy, Wolfram is a champion of cellular automata--256 "programs" governed by simple nonmathematical rules. He points out that even the most complex equations fail to accurately model biological systems, but the simplest cellular automata can produce results straight out of nature--tree branches, stream eddies, and leopard spots, for instance. The graphics in A New Kind of Science show striking resemblance to the patterns we see in nature every day. Wolfram wrote the book in a distinct style meant to make it easy to read, even for nontechies; a basic familiarity with logic is helpful but not essential. Readers will find themselves swept away by the elegant simplicity of Wolfram's ideas and the accidental artistry of the cellular automaton models. Whether or not Wolfram's revolution ultimately gives us the keys to the universe, his new science is absolutely awe-inspiring. --Therese Littleton

    Together, how do these distort and deform modern political geographies and produce new territories in their own image?In The Stack, Benjamin Bratton proposes that these different genres of computation—smart grids, cloud platforms, mobile apps, smart cities, the Internet of Things, automation—can be seen not as so many species evolving on their own, but as forming a coherent whole: an accidental megastructure called The Stack that is both a computational apparatus and a new governing architecture. We are inside The Stack and it is inside of us. In an account that is both theoretical and technical, drawing on political philosophy, architectural theory, and software studies, Bratton explores six layers of The Stack: Earth, Cloud, City, Address, Interface, User. Each is mapped on its own terms and understood as a component within the larger whole built from hard and soft systems intermingling—not only computational forms but also social, human, and physical forces. This model, informed by the logic of the multilayered structure of protocol “stacks,” in which network technologies operate within a modular and vertical order, offers a comprehensive image of our emerging infrastructure and a platform for its ongoing reinvention. The Stack is an interdisciplinary design brief for a new geopolitics that works with and for planetary-scale computation. Interweaving the continental, urban, and perceptual scales, it shows how we can better build, dwell within, communicate with, and govern our worlds.

    She ended up becoming so closely connected to Anonymous that the tricky story of her inside–outside status as Anon confidante, interpreter, and erstwhile mouthpiece forms one of the themes of this witty and entirely engrossing book.The narrative brims with details unearthed from within a notoriously mysterious subculture, whose semi-legendary tricksters—such as Topiary, tflow, Anachaos, and Sabu—emerge as complex, diverse, politically and culturally sophisticated people. Propelled by years of chats and encounters with a multitude of hackers, including imprisoned activist Jeremy Hammond and the double agent who helped put him away, Hector Monsegur, Hacker, Hoaxer, Whistleblower, Spy is filled with insights into the meaning of digital activism and little understood facets of culture in the Internet age, including the history of “trolling,” the ethics and metaphysics of hacking, and the origins and manifold meanings of “the lulz.”

    When we make mistakes, we must calm the cognitive dissonance that jars our feelings of self-worth. And so we create fictions that absolve us of responsibility, restoring our belief that we are smart, moral, and right -- a belief that often keeps us on a course that is dumb, immoral, and wrong. Backed by years of research and delivered in lively, energetic prose, Mistakes Were Made (But Not by Me) offers a fascinating explanation of self-deception -- how it works, the harm it can cause, and how we can overcome it.

    Authors Drew Conway and John Myles White help you understand machine learning and statistics tools through a series of hands-on case studies, instead of a traditional math-heavy presentation.Each chapter focuses on a specific problem in machine learning, such as classification, prediction, optimization, and recommendation. Using the R programming language, you'll learn how to analyze sample datasets and write simple machine learning algorithms. "Machine Learning for Hackers" is ideal for programmers from any background, including business, government, and academic research.Develop a naive Bayesian classifier to determine if an email is spam, based only on its textUse linear regression to predict the number of page views for the top 1,000 websitesLearn optimization techniques by attempting to break a simple letter cipherCompare and contrast U.S. Senators statistically, based on their voting recordsBuild a "whom to follow" recommendation system from Twitter data

    In the beginning was Josh Levine, an idealistic programming genius who dreamed of wresting control of the market from the big exchanges that, again and again, gave the giant institutions an advantage over the little guy. Levine created a computerized trading hub named Island where small traders swapped stocks, and over time his invention morphed into a global electronic stock market that sent trillions in capital through a vast jungle of fiber-optic cables. By then, the market that Levine had sought to fix had turned upside down, birthing secretive exchanges called dark pools and a new species of trading machines that could think, and that seemed, ominously, to be slipping the control of their human masters. Dark Pools is the fascinating story of how global markets have been hijacked by trading robots--many so self-directed that humans can't predict what they'll do next.

      Along the way, he reveals the untold story of Hans Asperger, the father of Asperger’s syndrome, whose “little professors” were targeted by the darkest social-engineering experiment in human history; exposes the covert campaign by child psychiatrist Leo Kanner to suppress knowledge of the autism spectrum for fifty years; and casts light on the growing movement of "neurodiversity" activists seeking respect, support, technological innovation, accommodations in the workplace and in education, and the right to self-determination for those with cognitive differences.

    This book synthesizes these recent advances and makes them accessible to first-year graduate students. James Hamilton provides the first adequate text-book treatments of important innovations such as vector autoregressions, generalized method of moments, the economic and statistical consequences of unit roots, time-varying variances, and nonlinear time series models. In addition, he presents basic tools for analyzing dynamic systems (including linear representations, autocovariance generating functions, spectral analysis, and the Kalman filter) in a way that integrates economic theory with the practical difficulties of analyzing and interpreting real-world data. Time Series Analysis fills an important need for a textbook that integrates economic theory, econometrics, and new results.The book is intended to provide students and researchers with a self-contained survey of time series analysis. It starts from first principles and should be readily accessible to any beginning graduate student, while it is also intended to serve as a reference book for researchers.-- "Journal of Economics"