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Inequality, Democracy, and Economic Development

ISBN: , SKU: , AUTHOR: Midlarsky, Manus I., PUBLISHER: Cambridge University Press, The relationship between inequality and democracy is a compelling one for the contemporary social scientist. This book addresses questions raised as early as the time of Aristotle, and continue through Marx to the present day. Theories of inequality in relation to democracy are explored, and the book focuses on the sources of democracy, the relationship between economic development and thresholds of democracy, and finally responses to democratization. As the gap between rich and poor widens within and between nations, the subject of this book becomes increasingly important worldwide.

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The Cambridge Companion to Chomsky

ISBN: , SKU: , AUTHOR: McGilvray, James, PUBLISHER: Cambridge University Press, Noam Chomsky is one of the most influential thinkers of modern times. The most cited writer in the humanities, his work has revolutionized the field of linguistics, and has dominated many other disciplines including politics and the philosophy of mind and human nature. This Companion brings together a team of leading linguists, philosophers, cognitive scientists and political theorists to consolidate the disparate strands of Chomsky's thought into one accessible volume and an essential guide to one of the leading intellectual figures of our time.

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Mining the Web: Discovering Knowledge from Hypertext Data

ISBN: , SKU: , AUTHOR: Chakrabarti, Soumen, PUBLISHER: Morgan Kaufmann Publishers, Mining the Web: Discovering Knowledge from Hypertext Data is the first book devoted entirely to techniques for producing knowledge from the vast body of unstructured Web data. Building on an initial survey of infrastructural issues-including Web crawling and indexing-Chakrabarti examines low-level machine learning techniques as they relate specifically to the challenges of Web mining. He then devotes the final part of the book to applications that unite infrastructure and analysis to bring machine learning to bear on systematically acquired and stored data. Here the focus is on results: the strengths and weaknesses of these applications, along with their potential as foundations for further progress. From Chakrabarti's work-painstaking, critical, and forward-looking-readers will gain the theoretical and practical understanding they need to contribute to the Web mining effort. * A comprehensive, critical exploration of statistics-based attempts to make sense of Web Mining. * Details the special challenges associated with analyzing unstructured and semi-structured data. * Looks at how classical Information Retrieval techniques have been modified for use with Web data. * Focuses on today's dominant learning methods: clustering and classification, hyperlink analysis, and supervised and semi-supervised learning. * Analyzes current applications for resource discovery and social network analysis. * An excellent way to introduce students to especially vital applications of data mining and machine learning technology.

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