This book teaches the principles of natural language processing and covers linguistics issues. It also details the language-processing functions involved, including part-of-speech tagging using rules and stochastic techniques. A key feature of the book is the author's hands-on approach throughout, with extensive exercises, sample code in Prolog and Perl, and a detailed introduction to Prolog. The book is suitable for researchers and students of natural language processing and computational linguistics.

The areas of natural language processing and computational linguistics have continued to grow in recent years, driven by the demand to automatically process text and spoken data. With the processing power and techniques now available, research is scaling up from lab prototypes to real-world, proven applications. This book teaches the principles of natural language processing, first covering practical linguistics issues such as encoding and annotation schemes, defining words, tokens and parts of speech and morphology, as well as key concepts in machine learning, such as entropy, regression and classification, which are used throughout the book. It then details the language-processing functions involved, including part-of-speech tagging using rules and stochastic techniques, using Prolog to write phase-structure grammars, syntactic formalisms and parsing techniques, semantics, predicate logic and lexical semantics and analysis of discourse and applications in dialogue systems. A key feature of the book is the author's hands-on approach throughout, with sample code in Prolog and Perl, extensive exercises, and a detailed introduction to Prolog. The reader is supported with a companion website that contains teaching slides, programs and additional material. The second edition is a complete revision of the techniques exposed in the book to reflect advances in the field the author redesigned or updated all the chapters, added two new ones and considerably expanded the sections on machine-learning techniques.

Prolog is a programming language, but a rather unusual one. Prolog'' is short for Programming with Logic'', and the link with logic gives Prolog its special character. At the heart of Prolog lies a surprising idea: don't tell the computer what to do. Instead, describe situations of interest, and compute by asking questions. Prolog will logically deduce new facts about the situations and give its deductions back to us as answers. Why learn Prolog? For a start, its say what the problem is, rather than how to solve it'' stance, means that it is a very high level language, good for knowledge rich applications such as artificial intelligence, natural language processing, and the semantic web. So by studying Prolog, you gain insight into how sophisticated tasks can be handled computationally. Moreover, Prolog requires a different mindset. You have to learn to see problems from a new perspective, declaratively rather than procedurally. Acquiring this mindset, and learning to appreciate the links between logic and programming, makes the study of Prolog both challenging and rewarding. Learn Prolog Now! is a practical introduction to this fascinating language. Freely available as a web-book since 2002 (see www.learnprolognow.org) Learn Prolog Now! has became one of the most popular introductions to the Prolog programming language, an introduction prized for its clarity and down-to-earth approach. It is widely used as a textbook at university departments around the world, and even more widely used for self study. College Publications is proud to present here the first hard-copy version of this online classic. Carefully revised in the light of reader's feedback, and now with answers to all the exercises, here you will find the essential material required to help you learn Prolog now.

"This book provides pertinent and vital information that researchers, postgraduate, doctoral students, and practitioners are seeking for learning about the latest discoveries and advances in NLP methodologies and applications of NLP"--Provided by publisher.

Linguistics, Literature and Cultural Studies are the three main research areas within Philology. Scientific production, such as conferences and journals, has tended towards specialization, and has been traditionally classified according to separate disciplines and languages. However, this volume offers a holistic view of the wide area of Philology, therefore allowing the permeability of the three areas mentioned above. As such, this book shows that the line that separates Linguistics, Literature and Cultural Studies is actually very thin. This volume is composed of a miscellanea of philological studies dealing with various trends in Modern Language research. It looks at three languages in particular: Spanish, English and French, with a special relevance to the first two.

A survey of computational methods for understanding, generating, and manipulating human language, which offers a synthesis of classical representations and algorithms with contemporary machine learning techniques. This textbook provides a technical perspective on natural language processing—methods for building computer software that understands, generates, and manipulates human language. It emphasizes contemporary data-driven approaches, focusing on techniques from supervised and unsupervised machine learning. The first section establishes a foundation in machine learning by building a set of tools that will be used throughout the book and applying them to word-based textual analysis. The second section introduces structured representations of language, including sequences, trees, and graphs. The third section explores different approaches to the representation and analysis of linguistic meaning, ranging from formal logic to neural word embeddings. The final section offers chapter-length treatments of three transformative applications of natural language processing: information extraction, machine translation, and text generation. End-of-chapter exercises include both paper-and-pencil analysis and software implementation. The text synthesizes and distills a broad and diverse research literature, linking contemporary machine learning techniques with the field's linguistic and computational foundations. It is suitable for use in advanced undergraduate and graduate-level courses and as a reference for software engineers and data scientists. Readers should have a background in computer programming and college-level mathematics. After mastering the material presented, students will have the technical skill to build and analyze novel natural language processing systems and to understand the latest research in the field.

A gentle introduction to programming for students and researchers interested in conducting computer-based analysis in linguistics, this book is an ideal starting point for linguists approaching programming for the first time. Assuming no background knowledge of programming, the author introduces basic notions and techniques needed for linguistics programming and helps readers to develop their understanding of electronic texts.The book includes many examples based on diverse topics in linguistics in order to demonstrate the applicability of the concepts at the heart of programming. Practical examples are designed to help the reader to:*Identify basic issues in handling language data, including Unicode processing*Conduct simple analyses in morphology/morphosyntax, and phonotactics*Understanding techniques for matching linguistic patterns*Learn to convert data into formats and data structures suitable for linguistic analysis*Create frequency lists from corpus materials to gather basic descriptive statistics on texts*Understand, obtain and 'clean up' web-based data*Design graphical user interfaces for writing more efficient and easy-to-use analysis tools.Two different types of exercise help readers to either learn to interpret and understand illustrative sample code, or to develop algorithmic thinking and solution strategies through turning a series of instructions into sample programs. Readers will be equipped with the necessary tools for designing their own extended projects.Key Features:*Ideal introduction for students of linguistics attempting to process corpus materials or literary texts for dissertations, theses or advanced research work*Linguistic examples throughout the text clearly demonstrate the application of programming theory and techniques*Coverage ranging from basic to more complex topics and methodologies enables the reader to progress at their own pace*Two chapters on the advantages of modularity and associated issues provid