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Introduction to Information Retrieval
Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. 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. Slides and additional exercises (with solutions for lecturers) are also available through the book's supporting website to help course instructors prepare their lectures.
Foundations of Statistical Natural Language Processing
Statistical approaches to processing natural language text have become dominant in recent years. This foundational text is the first comprehensive introduction to statistical natural language processing (NLP) to appear. The book contains all the theory and algorithms needed for building NLP tools. It provides broad but rigorous coverage of mathematical and linguistic foundations, as well as detailed discussion of statistical methods, allowing students and researchers to construct their own implementations. The book covers collocation finding, word sense disambiguation, probabilistic parsing, information retrieval, and other applications.
Dependency Parsing
Dependency-based methods for syntactic parsing have become increasingly popular in natural language processing in recent years. This book gives a thorough introduction to the methods that are most widely used today. After an introduction to dependency grammar and dependency parsing, followed by a formal characterization of the dependency parsing problem, the book surveys the three major classes of parsing models that are in current use: transition-based, graph-based, and grammar-based models. It continues with a chapter on evaluation and one on the comparison of different methods, and it closes with a few words on current trends and future prospects of dependency parsing. The book presupposes a knowledge of basic concepts in linguistics and computer science, as well as some knowledge of parsing methods for constituency-based representations. Table of Contents: Introduction / Dependency Parsing / Transition-Based Parsing / Graph-Based Parsing / Grammar-Based Parsing / Evaluation / Comparison / Final Thoughts
Human-in-the-Loop Machine Learning
Machine learning applications perform better with human feedback. Keeping the right people in the loop improves the accuracy of models, reduces errors in data, lowers costs, and helps you ship models faster. Human-in-the-loop machine learning lays out methods for humans and machines to work together effectively. You'll find best practices on selecting sample data for human feedback, quality control for human annotations, and designing annotation interfaces. You'll learn to dreate training data for labeling, object detection, and semantic segmentation, sequence labeling, and more. The book starts with the basics and progresses to advanced techniques like transfer learning and self-supervision within annotation workflows.
Complex Predicates and Information Spreading in LFG
This book provides a simple but precise framework for describing complex predicates and related constructions, and applies it principally to the analysis of complex predicates in Romance, and certain serial verb constructions in Tariana and Miskitu. The authors argue for replacing the projection architecture of LFG with a notion of differential information spreading within a unified feature structure. Another important feature is the use of the conception of argument-structure in Chris Manning's Ergativity to facilitate the description of how complex predicates are assembled. In both of these aspects the result is a framework that preserves the descriptive parsimony of LFG while taking on key ideas from HPSG.
Ergativity
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Statistical Methods for Speech Recognition
This book reflects decades of important research on the mathematical foundations of speech recognition. It focuses on underlying statistical techniques such as hidden Markov models, decision trees, the expectation-maximization algorithm, information theoretic goodness criteria, maximum entropy probability estimation, parameter and data clustering, and smoothing of probability distributions. The author's goal is to present these principles clearly in the simplest setting, to show the advantages of self-organization from real data, and to enable the reader to apply the techniques. Bradford Books imprint
NeuroWisdom
Perfect for readers of How God Changes Your Brain, two researchers present over thirty brain exercises to help readers generate happiness and success, in business and in life. ”This remarkable book translates state-of-the art neuroscience into practical techniques that rapidly promote personal transformation. If you want to double your happiness and your income, start using these powerful brain-changing exercises today!” ―John Assaraf, New York Times bestselling author and CEO of NeuroGym Adapted from a business school course they created for professionals, bestselling author Mark Waldman and Chris Manning present simple brain exercises, based on the latest neuroscience research, to gu...
The World's Newest Profession
In The World's Newest Profession Christopher McKenna offers a history of management consulting in the twentieth century. Although management consulting may not yet be a recognized profession, the leading consulting firms have been advising and reshaping the largest organizations in the world since the 1920s. This groundbreaking study details how the elite consulting firms, including McKinsey & Company and Booz Allen & Hamilton, expanded after US regulatory changes during the 1930s, how they changed giant corporations, nonprofits, and the state during the 1950s, and why consultants became so influential in the global economy after 1960. As they grew in number, consultants would introduce organizations to 'corporate culture' and 'decentralization' but they faced vilification for their role in the Enron crisis and for legitimating corporate blunders. Through detailed case studies based on unprecedented access to internal files and personal interviews, The World's Newest Profession explores how management consultants came to be so influential within our culture and explains exactly what consultants really do in the global economy.
