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Natural language processing (Computer science)

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Natural language processing (Computer science)

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"A problem-solution guide to encountering various NLP tasks utilizing Java open source libraries and cloud-based solutions Key Features Perform simple-to-complex NLP text processing tasks using modern Java libraries Extract relationships between different text complexities using a problem-solution approach Utilize cloud-based APIs to perform machine translation operations Book Description Natural Language Processing (NLP) has become one of the prime technologies for processing very large amounts of unstructured data from disparate information sources. This book includes a wide set of recipes and quick methods that solve challenges in text syntax, semantics, and speech tasks. At the beginning of the book, you'll learn important NLP techniques, such as identifying parts of speech, tagging words, and analyzing word semantics. You will learn how to perform lexical analysis and use machine learning techniques to speed up NLP operations. With independent recipes, you will explore techniques for customizing your existing NLP engines/models using Java libraries such as OpenNLP and the Stanford NLP library. You will also learn how to use NLP processing features from cloud-based sources, including Google and Amazon Web Services (AWS). You will master core tasks, such as stemming, lemmatization, part-of-speech tagging, and named entity recognition. You will also learn about sentiment analysis, semantic text similarity, language identification, machine translation, and text summarization. By the end of this book, you will be ready to become a professional NLP expert using a problem-solution approach to analyze any sort of text, sentence, or semantic word. What you will learn Explore how to use tokenizers in NLP processing Implement NLP techniques in machine learning and deep learning applications Identify sentences within text and learn how to train specialized NER models Learn how to classify documents and perform sentiment analysis Find semantic similarities between text elements and extract text from a variety of sources Preprocess text from a variety of data sources Learn how to identify and translate languages Who this book is for This book is for data scientists, NLP engineers, and machine learning developers who want to perform their work on linguistic applications faster with the use of popular libraries on JVM machines. This book will help you build real-world NLP applications using a recipe-based approach. Prior knowledge of Natural Language Processing basics and Java programming is expected." -- Publisher's description.

Natural language processing (Computer science)

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Contains information about many core facets of modern computational-linguistic work. This book is suitable for people interested in learning about strategies that are best suited for developing computational-linguistic capabilities for lesser-studied languages - either 'from scratch' or using components developed for other languages.

Computational linguistics --- Natural language processing (Computer science)

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This volume contains 17 articles, developed from papers that were chosen from among the 44 presentations of work on NooJ presented at the 2013 International NooJ Conference in Saarbrücken in June, 2013. NooJ is a linguistic development environment that allows linguists to formalize a wide gamut of linguistic phenomena, and then test, adapt, share and accumulate each elementary description to build linguistic ""modules"", that is, structured libraries of linguistic resources. NooJ is also used ...

Computational linguistics --- Natural language processing (Computer science)