Natural Language Processing Using Very Large Corpora
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Natural Language Processing Using Very Large Corpora
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Author : S. Armstrong
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-04-17
Natural Language Processing Using Very Large Corpora written by S. Armstrong and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-17 with Language Arts & Disciplines categories.
ABOUT THIS BOOK This book is intended for researchers who want to keep abreast of cur rent developments in corpus-based natural language processing. It is not meant as an introduction to this field; for readers who need one, several entry-level texts are available, including those of (Church and Mercer, 1993; Charniak, 1993; Jelinek, 1997). This book captures the essence of a series of highly successful work shops held in the last few years. The response in 1993 to the initial Workshop on Very Large Corpora (Columbus, Ohio) was so enthusias tic that we were encouraged to make it an annual event. The following year, we staged the Second Workshop on Very Large Corpora in Ky oto. As a way of managing these annual workshops, we then decided to register a special interest group called SIGDAT with the Association for Computational Linguistics. The demand for international forums on corpus-based NLP has been expanding so rapidly that in 1995 SIGDAT was led to organize not only the Third Workshop on Very Large Corpora (Cambridge, Mass. ) but also a complementary workshop entitled From Texts to Tags (Dublin). Obviously, the success of these workshops was in some measure a re flection of the growing popularity of corpus-based methods in the NLP community. But first and foremost, it was due to the fact that the work shops attracted so many high-quality papers.
Using Large Corpora
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Author : Armstrong-Warwick Armstrong
language : en
Publisher: MIT Press
Release Date : 1994
Using Large Corpora written by Armstrong-Warwick Armstrong and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with Business & Economics categories.
Using Large Corpora identifies new data-oriented methods for organizing and analyzing large corpora and describes the potential results that the use of large corpora offers. Today, large corpora consisting of hundreds of millions or even billions of words, along with new empirical and statistical methods for organizing and analyzing these data, promise new insights into the use of language. Already, the data extracted from these large corpora reveal that language use is more flexible and complex than most rule-based systems have tried to account for, providing a basis for progress in the performance of Natural Language Processing systems. Using Large Corpora identifies these new data-oriented methods and describes the potential results that the use of large corpora offers. The research described shows that the new methods may offer solutions to key issues of acquisition (automatically identifying and coding information), coverage (accounting for all of the phenomena in a given domain), robustness (accommodating real data that may be corrupt or not accounted for in the model), and extensibility (applying the model and data to a new domain, text, or problem). There are chapters on lexical issues, issues in syntax, and translation topics, as well discussions of the statistics-based vs. rule-based debate. ACL-MIT Series in Natural Language Processing.
Building And Using Comparable Corpora For Multilingual Natural Language Processing
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Author : Serge Sharoff
language : en
Publisher: Springer Nature
Release Date : 2023-08-23
Building And Using Comparable Corpora For Multilingual Natural Language Processing written by Serge Sharoff and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-23 with Computers categories.
This book provides a comprehensive overview of methods to build comparable corpora and of their applications, including machine translation, cross-lingual transfer, and various kinds of multilingual natural language processing. The authors begin with a brief history on the topic followed by a comparison to parallel resources and an explanation of why comparable corpora have become more widely used. In particular, they provide the basis for the multilingual capabilities of pre-trained models, such as BERT or GPT. The book then focuses on building comparable corpora, aligning their sentences to create a database of suitable translations, and using these sentence translations to produce dictionaries and term banks. Then, it is explained how comparable corpora can be used to build machine translation engines and to develop a wide variety of multilingual applications.
Natural Language Processing With Python Cookbook
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Author : Krishna Bhavsar
language : en
Publisher:
Release Date : 2017-11-24
Natural Language Processing With Python Cookbook written by Krishna Bhavsar and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-24 with Computers categories.
Learn the tricks and tips that will help you design Text Analytics solutionsAbout This Book* Independent recipes that will teach you how to efficiently perform Natural Language Processing in Python* Use dictionaries to create your own named entities using this easy-to-follow guide* Learn how to implement NLTK for various scenarios with the help of example-rich recipes to take you beyond basic Natural Language ProcessingWho This Book Is ForThis book is intended for data scientists, data analysts, and data science professionals who want to upgrade their existing skills to implement advanced text analytics using NLP. Some basic knowledge of Natural Language Processing is recommended.What You Will Learn* Explore corpus management using internal and external corpora* Learn WordNet usage and a couple of simple application assignments using WordNet* Operate on raw text* Learn to perform tokenization, stemming, lemmatization, and spelling corrections, stop words removals, and more* Understand regular expressions for pattern matching* Learn to use and write your own POS taggers and grammars* Learn to evaluate your own trained models* Explore Deep Learning techniques in NLP* Generate Text from Nietzsche's writing using LSTM* Utilize the BABI dataset and LSTM to model episodesIn DetailNatural Language Processing (NLP) is a field of computer science, artificial intelligence, and computational linguistics concerned with the interactions between computers and human (natural) languages; in particular, it's about programming computers to fruitfully process large natural language corpora.This book includes unique recipes that will teach you various aspects of performing Natural Language Processing with NLTK-the leading Python platform for the task. You will come across various recipes during the course, covering (among other topics) natural language understanding, Natural Language Processing, and syntactic analysis. You will learn how to understand language, plan sentences, and work around various ambiguities. You will learn how to efficiently use NLTK and implement text classification, identify parts of speech, tag words, and more. You will also learn how to analyze sentence structures and master lexical analysis, syntactic and semantic analysis, pragmatic analysis, and the application of deep learning techniques.By the end of this book, you will have all the knowledge you need to implement Natural Language Processing with Python.Style and ApproachThis book's rich collection of recipes will come in handy when you are working with Natural Language Processing with Python. Addressing your common and not-so-common pain points, this is a book that you must have on the shelf.
Natural Language Processing With Python
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Author : Steven Bird
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2009-06-12
Natural Language Processing With Python written by Steven Bird and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-06-12 with Computers categories.
This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication. Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify "named entities" Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligence This book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.
Proceedings Of The 1999 Joint Sigdat Conference On Empirical Methods In Natural Language Processing And Very Large Corpora
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Author : Pascale Fung
language : en
Publisher:
Release Date : 1999
Proceedings Of The 1999 Joint Sigdat Conference On Empirical Methods In Natural Language Processing And Very Large Corpora written by Pascale Fung and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Computational linguistics categories.
Python Natural Language Processing
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Author : Jalaj Thanaki
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-07-31
Python Natural Language Processing written by Jalaj Thanaki and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-31 with Computers categories.
Leverage the power of machine learning and deep learning to extract information from text data About This Book Implement Machine Learning and Deep Learning techniques for efficient natural language processing Get started with NLTK and implement NLP in your applications with ease Understand and interpret human languages with the power of text analysis via Python Who This Book Is For This book is intended for Python developers who wish to start with natural language processing and want to make their applications smarter by implementing NLP in them. What You Will Learn Focus on Python programming paradigms, which are used to develop NLP applications Understand corpus analysis and different types of data attribute. Learn NLP using Python libraries such as NLTK, Polyglot, SpaCy, Standford CoreNLP and so on Learn about Features Extraction and Feature selection as part of Features Engineering. Explore the advantages of vectorization in Deep Learning. Get a better understanding of the architecture of a rule-based system. Optimize and fine-tune Supervised and Unsupervised Machine Learning algorithms for NLP problems. Identify Deep Learning techniques for Natural Language Processing and Natural Language Generation problems. In Detail This book starts off by laying the foundation for Natural Language Processing and why Python is one of the best options to build an NLP-based expert system with advantages such as Community support, availability of frameworks and so on. Later it gives you a better understanding of available free forms of corpus and different types of dataset. After this, you will know how to choose a dataset for natural language processing applications and find the right NLP techniques to process sentences in datasets and understand their structure. You will also learn how to tokenize different parts of sentences and ways to analyze them. During the course of the book, you will explore the semantic as well as syntactic analysis of text. You will understand how to solve various ambiguities in processing human language and will come across various scenarios while performing text analysis. You will learn the very basics of getting the environment ready for natural language processing, move on to the initial setup, and then quickly understand sentences and language parts. You will learn the power of Machine Learning and Deep Learning to extract information from text data. By the end of the book, you will have a clear understanding of natural language processing and will have worked on multiple examples that implement NLP in the real world. Style and approach This book teaches the readers various aspects of natural language Processing using NLTK. It takes the reader from the basic to advance level in a smooth way.
Natural Language Processing For Corpus Linguistics
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Author : Jonathan Dunn
language : en
Publisher: Cambridge University Press
Release Date : 2022-03-31
Natural Language Processing For Corpus Linguistics written by Jonathan Dunn and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-31 with Language Arts & Disciplines categories.
Corpus analysis can be expanded and scaled up by incorporating computational methods from natural language processing. This Element shows how text classification and text similarity models can extend our ability to undertake corpus linguistics across very large corpora. These computational methods are becoming increasingly important as corpora grow too large for more traditional types of linguistic analysis. We draw on five case studies to show how and why to use computational methods, ranging from usage-based grammar to authorship analysis to using social media for corpus-based sociolinguistics. Each section is accompanied by an interactive code notebook that shows how to implement the analysis in Python. A stand-alone Python package is also available to help readers use these methods with their own data. Because large-scale analysis introduces new ethical problems, this Element pairs each new methodology with a discussion of potential ethical implications.
Handbook Of Natural Language Processing
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Author : Nitin Indurkhya
language : en
Publisher: CRC Press
Release Date : 2010-02-22
Handbook Of Natural Language Processing written by Nitin Indurkhya and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-02-22 with Business & Economics categories.
The Handbook of Natural Language Processing, Second Edition presents practical tools and techniques for implementing natural language processing in computer systems. Along with removing outdated material, this edition updates every chapter and expands the content to include emerging areas, such as sentiment analysis.New to the Second EditionGreater
Speech And Language Processing
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Author : Dan Jurafsky
language : en
Publisher: Prentice Hall
Release Date : 2009
Speech And Language Processing written by Dan Jurafsky and has been published by Prentice Hall this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Automatic speech recognition categories.
This book takes an empirical approach to language processing, based on applying statistical and other machine-learning algorithms to large corpora. Methodology boxes are included in each chapter. Each chapter is built around one or more worked examples to demonstrate the main idea of the chapter. Covers the fundamental algorithms of various fields, whether originally proposed for spoken or written language to demonstrate how the same algorithm can be used for speech recognition and word-sense disambiguation. Emphasis on web and other practical applications. Emphasis on scientific evaluation. Useful as a reference for professionals in any of the areas of speech and language processing.