Finite-State Methods and Natural Language Processing

Finite-State Methods and Natural Language Processing
Author: Anssi Yli-Jyrä
Publisher: Springer Science & Business Media
Total Pages: 324
Release: 2006-12-07
Genre: Computers
ISBN: 3540354670

This book constitutes the thoroughly refereed post-proceedings of the 5th International Workshop on Finite-State Methods in Natural Language Processing, FSMNLP 2005, held in Helsinki, Finland, September 2005. The book presents 24 revised full papers and seven revised poster papers together with two invited contributions and abstracts of six software demos. Topics include morphology, optimality theory, some special FSM families, weighted FSM algorithms, FSM representations, exploration, ordered structures, and surface parsing.

Finite-state Methods and Natural Language Processing

Finite-state Methods and Natural Language Processing
Author: Jakub Piskorski
Publisher: IOS Press
Total Pages: 248
Release: 2009
Genre: Computers
ISBN: 158603975X

Contains papers that cover a range of Natural Language Processing (NLP) applications, including machine learning and translation, logic, computational phonology, morphology and semantics, data mining, information extraction and disambiguation, as well as programming, optimization and compression of finite-state networks.

Finite-State Techniques

Finite-State Techniques
Author: Stoyan Mihov
Publisher: Cambridge University Press
Total Pages: 316
Release: 2019-08-01
Genre: Computers
ISBN: 1108621139

Finite-state methods are the most efficient mechanisms for analysing textual and symbolic data, providing elegant solutions for an immense number of practical problems in computational linguistics and computer science. This book for graduate students and researchers gives a complete coverage of the field, starting from a conceptual introduction and building to advanced topics and applications. The central finite-state technologies are introduced with mathematical rigour, ranging from simple finite-state automata to transducers and bimachines as 'input-output' devices. Special attention is given to the rich possibilities of simplifying, transforming and combining finite-state devices. All algorithms presented are accompanied by full correctness proofs and executable source code in a new programming language, C(M), which focuses on transparency of steps and simplicity of code. Thus, by enabling readers to obtain a deep formal understanding of the subject and to put finite-state methods to real use, this book closes the gap between theory and practice.

Introduction to Natural Language Processing

Introduction to Natural Language Processing
Author: Jacob Eisenstein
Publisher: MIT Press
Total Pages: 535
Release: 2019-10-01
Genre: Computers
ISBN: 0262042843

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.

Multilingual Natural Language Processing Applications

Multilingual Natural Language Processing Applications
Author: Daniel Bikel
Publisher: IBM Press
Total Pages: 829
Release: 2012-05-11
Genre: Business & Economics
ISBN: 0137047819

Multilingual Natural Language Processing Applications is the first comprehensive single-source guide to building robust and accurate multilingual NLP systems. Edited by two leading experts, it integrates cutting-edge advances with practical solutions drawn from extensive field experience. Part I introduces the core concepts and theoretical foundations of modern multilingual natural language processing, presenting today’s best practices for understanding word and document structure, analyzing syntax, modeling language, recognizing entailment, and detecting redundancy. Part II thoroughly addresses the practical considerations associated with building real-world applications, including information extraction, machine translation, information retrieval/search, summarization, question answering, distillation, processing pipelines, and more. This book contains important new contributions from leading researchers at IBM, Google, Microsoft, Thomson Reuters, BBN, CMU, University of Edinburgh, University of Washington, University of North Texas, and others. Coverage includes Core NLP problems, and today’s best algorithms for attacking them Processing the diverse morphologies present in the world’s languages Uncovering syntactical structure, parsing semantics, using semantic role labeling, and scoring grammaticality Recognizing inferences, subjectivity, and opinion polarity Managing key algorithmic and design tradeoffs in real-world applications Extracting information via mention detection, coreference resolution, and events Building large-scale systems for machine translation, information retrieval, and summarization Answering complex questions through distillation and other advanced techniques Creating dialog systems that leverage advances in speech recognition, synthesis, and dialog management Constructing common infrastructure for multiple multilingual text processing applications This book will be invaluable for all engineers, software developers, researchers, and graduate students who want to process large quantities of text in multiple languages, in any environment: government, corporate, or academic.

Natural Language Processing and Text Mining

Natural Language Processing and Text Mining
Author: Anne Kao
Publisher: Springer Science & Business Media
Total Pages: 272
Release: 2007-03-06
Genre: Computers
ISBN: 1846287545

Natural Language Processing and Text Mining not only discusses applications of Natural Language Processing techniques to certain Text Mining tasks, but also the converse, the use of Text Mining to assist NLP. It assembles a diverse views from internationally recognized researchers and emphasizes caveats in the attempt to apply Natural Language Processing to text mining. This state-of-the-art survey is a must-have for advanced students, professionals, and researchers.

Natural Language Processing of Semitic Languages

Natural Language Processing of Semitic Languages
Author: Imed Zitouni
Publisher: Springer Science & Business
Total Pages: 477
Release: 2014-04-22
Genre: Computers
ISBN: 3642453589

Research in Natural Language Processing (NLP) has rapidly advanced in recent years, resulting in exciting algorithms for sophisticated processing of text and speech in various languages. Much of this work focuses on English; in this book we address another group of interesting and challenging languages for NLP research: the Semitic languages. The Semitic group of languages includes Arabic (206 million native speakers), Amharic (27 million), Hebrew (7 million), Tigrinya (6.7 million), Syriac (1 million) and Maltese (419 thousand). Semitic languages exhibit unique morphological processes, challenging syntactic constructions and various other phenomena that are less prevalent in other natural languages. These challenges call for unique solutions, many of which are described in this book. The 13 chapters presented in this book bring together leading scientists from several universities and research institutes worldwide. While this book devotes some attention to cutting-edge algorithms and techniques, its primary purpose is a thorough explication of best practices in the field. Furthermore, every chapter describes how the techniques discussed apply to Semitic languages. The book covers both statistical approaches to NLP, which are dominant across various applications nowadays and the more traditional, rule-based approaches, that were proven useful for several other application domains. We hope that this book will provide a "one-stop-shop'' for all the requisite background and practical advice when building NLP applications for Semitic languages.

Recent Advances in Natural Language Processing III

Recent Advances in Natural Language Processing III
Author: Nicolas Nicolov
Publisher: John Benjamins Publishing
Total Pages: 418
Release: 2004-11-30
Genre: Language Arts & Disciplines
ISBN: 9027294682

This volume brings together revised versions of a selection of papers presented at the 2003 International Conference on “Recent Advances in Natural Language Processing”. A wide range of topics is covered in the volume: semantics, dialogue, summarization, anaphora resolution, shallow parsing, morphology, part-of-speech tagging, named entity, question answering, word sense disambiguation, information extraction. Various ‘state-of-the-art’ techniques are explored: finite state processing, machine learning (support vector machines, maximum entropy, decision trees, memory-based learning, inductive logic programming, transformation-based learning, perceptions), latent semantic analysis, constraint programming. The papers address different languages (Arabic, English, German, Slavic languages) and use different linguistic frameworks (HPSG, LFG, constraint-based DCG). This book will be of interest to those who work in computational linguistics, corpus linguistics, human language technology, translation studies, cognitive science, psycholinguistics, artificial intelligence, and informatics.