Text Processing In Java
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Natural Language Processing with Java
Author: Richard M. Reese
language: en
Publisher: Packt Publishing Ltd
Release Date: 2018-07-31
Explore various approaches to organize and extract useful text from unstructured data using Java Key Features Use deep learning and NLP techniques in Java to discover hidden insights in text Work with popular Java libraries such as CoreNLP, OpenNLP, and Mallet Explore machine translation, identifying parts of speech, and topic modeling Book Description Natural Language Processing (NLP) allows you to take any sentence and identify patterns, special names, company names, and more. The second edition of Natural Language Processing with Java teaches you how to perform language analysis with the help of Java libraries, while constantly gaining insights from the outcomes. You’ll start by understanding how NLP and its various concepts work. Having got to grips with the basics, you’ll explore important tools and libraries in Java for NLP, such as CoreNLP, OpenNLP, Neuroph, and Mallet. You’ll then start performing NLP on different inputs and tasks, such as tokenization, model training, parts-of-speech and parsing trees. You’ll learn about statistical machine translation, summarization, dialog systems, complex searches, supervised and unsupervised NLP, and more. By the end of this book, you’ll have learned more about NLP, neural networks, and various other trained models in Java for enhancing the performance of NLP applications. What you will learn Understand basic NLP tasks and how they relate to one another Discover and use the available tokenization engines Apply search techniques to find people, as well as things, within a document Construct solutions to identify parts of speech within sentences Use parsers to extract relationships between elements of a document Identify topics in a set of documents Explore topic modeling from a document Who this book is for Natural Language Processing with Java is for you if you are a data analyst, data scientist, or machine learning engineer who wants to extract information from a language using Java. Knowledge of Java programming is needed, while a basic understanding of statistics will be useful but not mandatory.
Introduction to Linguistic Annotation and Text Analytics
Author: Graham Wilcock
language: en
Publisher: Morgan & Claypool Publishers
Release Date: 2009
Linguistic annotation and text analytics are active areas of research and development, with academic conferences and industry events such as the Linguistic Annotation Workshops and the annual Text Analytics Summits. This book provides a basic introduction to both fields, and aims to show that good linguistic annotations are the essential foundation for good text analytics. After briefly reviewing the basics of XML, with practical exercises illustrating in-line and stand-off annotations, a chapter is devoted to explaining the different levels of linguistic annotations. The reader is encouraged to create example annotations using the WordFreak linguistic annotation tool. The next chapter shows how annotations can be created automatically using statistical NLP tools, and compares two sets of tools, the OpenNLP and Stanford NLP tools. The second half of the book describes different annotation formats and gives practical examples of how to interchange annotations between different formats using XSLT transformations. The two main text analytics architectures, GATE and UIMA, are then described and compared, with practical exercises showing how to configure and customize them. The final chapter is an introduction to text analytics, describing the main applications and functions including named entity recognition, coreference resolution and information extraction, with practical examples using both open source and commercial tools. Copies of the example files, scripts, and stylesheets used in the book are available from the companion website, located at http: //sites.morganclaypool.com/wilcock. Table of Contents: Working with XML / Linguistic Annotation / Using Statistical NLP Tools / Annotation Interchange / Annotation Architectures / Text Analytics
Text Processing in Java
This book teaches you how to master the subtle art of multilingual text processing and prevent text data corruption. It provides an introduction to natural language processing using Lucene and Solr. It gives you tools and techniques to manage large collections of text data, whether they come from news feeds, databases, or legacy documents. Each chapter contains executable programs that can also be used for text data forensics. Topics covered: Unicode code points Character encodings from ASCII and Big5 to UTF-8 and UTF-32LE Character normalization using International Components for Unicode (ICU) Java I/O, including working directly with zip, gzip, and tar files Regular expressions in Java Transporting text data via HTTP Parsing and generating XML, HTML, and JSON Using Lucene 4 for natural language search and text classification Search, spelling correction, and clustering with Solr 4 Other books on text processing presuppose much of the material covered in this book. They gloss over the details of transforming text from one format to another and assume perfect input data. The messy reality of raw text will have you reaching for this book again and again.