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Natural Language Processing with Java Cookbook电子书

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2人正在读 | 0人评论 9.8

作       者:Richard M. Reese

出  版  社:Packt Publishing

出版时间:2019-04-25

字       数:41.6万

所属分类: 进口书 > 外文原版书 > 电脑/网络

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A problem-solution guide to encounter 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’s 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, sentences, or semantic words. 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 the 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.
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About Packt

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Packt.com

Contributors

About the author

About the reviewer

Packt is searching for authors like you

Preface

Who this book is for

What this book covers

To get the most out of this book

Download the example code files

Conventions used

Sections

Getting ready

How to do it…

How it works…

There's more…

See also

Get in touch

Reviews

Preparing Text for Analysis and Tokenization

Technical requirements

Tokenization using the Java SDK

Getting ready

How to do it...

How it works...

Tokenization using OpenNLP

Getting ready

How to do it...

How it works...

See also

Tokenization using maximum entropy

Getting ready

How to do it...

How it works...

See also

Training a neural network tokenizer for specialized text

Getting ready

How to do it...

How it works...

There's more...

See also

Identifying the stem of a word

Getting ready

How to do it...

How it works...

See also

Training an OpenNLP lemmatization model

Getting ready

How to do it...

How it works...

There's more...

See also

Determining the lexical meaning of a word using OpenNLP

Getting ready

How to do it...

How it works...

See also

Removing stop words using LingPipe

Getting ready

How to do it...

How it works...

See also

Isolating Sentences within a Document

Technical requirements

Finding sentences using the Java core API

Getting ready

How to do it...

How it works...

See also

Performing SBD using the BreakIterator class

Getting ready

How to do it...

How it works...

There's more...

See also

Using OpenNLP to perform SBD

Getting ready

How to do it...

How it works...

There's more...

See also

Using the Stanford NLP API to perform SBD

Getting ready

How to do it...

How it works...

There's more...

See also

Using the LingPipe and chunking to perform SBD

Getting ready

How to do it...

How it works...

There's more...

See also

Performing SBD on specialized text

Getting ready

How to do it...

How it works...

See also

Training a neural network to perform SBD with specialized text

Getting ready

How to do it...

How it works...

See also

Performing Name Entity Recognition

Technical requirements

Using regular expressions to find entities

Getting ready

How to do it...

How it works...

There's more...

See also

Using chunks with regular expressions to identify entities

Getting ready

How to do it...

How it works...

There's more...

See also

Using OpenNLP to find entities in text

Getting ready

How to do it...

How it works...

There's more...

See also

Isolating multiple entities types

Getting ready

How to do it...

How it works...

See also

Using a CRF model to find entities in a document

Getting ready

How to do it...

How it works...

There's more...

See also

Using a chunker to find entities

Getting ready

How to do it...

How it works...

See also

Training a specialized NER model

Getting ready

How to do it...

How it works...

See also

Detecting POS Using Neural Networks

Technical requirements

Finding POS using tagging

Getting ready

How to do it...

How it works...

There's more...

See also

Using a chunker to find POS

Getting ready

How to do it...

How it works...

There's more...

See also

Using a tag dictionary

Getting ready

How to do it...

How it works...

There's more...

See also

Finding POS using the Penn Treebank

Getting ready

How to do it...

How it works...

There's more...

See also

Finding POS from textese

Getting ready

How to do it...

How it works...

There's more...

See also

Using a pipeline to perform tagging

Getting ready

How to do it...

How it works...

See also

Using a hidden Markov model to perform POS

Getting ready

How to do it...

How it works...

There's more...

See also

Training a specialized POS model

Getting ready

How to do it...

How it works...

See also

Performing Text Classification

Technical requirements

Training a maximum entropy model for text classification

Getting ready

How to do it...

How it works...

See also

Classifying documents using a maximum entropy model

Getting ready

How to do it...

How it works...

There's more...

See also

Classifying documents using the Stanford API

Getting ready

How to do it...

How it works...

There's more...

See also

Training a model to classify text using LingPipe

Getting ready

How to do it...

How it works...

See also

Using LingPipe to classify text

Getting ready

How to do it...

How it works...

There's more...

See also

Detecting spam

Getting ready

How to do it...

How it works...

There's more...

See also

Performing sentiment analysis on reviews

Getting ready

How to do it...

How it works...

There's more...

See also

Finding Relationships within Text

Technical requirements

Displaying parse trees graphically

Getting ready

How to do it...

How it works...

There's more...

See also

Using probabilistic context-free grammar to parse text

Getting ready

How to do it...

How it works...

There's more...

See also

Using OpenNLP to generate a parse tree

Getting ready

How to do it...

How it works...

There's more...

See also

Using the Google NLP API to parse text

Getting ready

How to do it...

How it works...

There's more...

See also

Identifying parent-child relationships in text

Getting ready

How to do it...

How it works...

There's more...

See also

Finding co-references in a sentence

Getting ready

How to do it...

How it works...

There's more...

See also

Language Identification and Translation

Technical requirements

Detecting the natural language in use using LingPipe

Getting ready

How to do it…

How it works…

There's more…

See also

Discovering supported languages using the Google API

Getting ready

How to do it…

How it works…

See also

Detecting the natural language in use using the Google API

Getting ready

How to do it…

How it works…

There's more…

See also

Language translation using Google

Getting ready

How to do it…

How it works…

There's more…

See also

Language detection and translation using Amazon AWS

Getting ready

How to do it…

How it works…

There's more…

See also

Converting text to speech using the Google Cloud Text-to-Speech API

Getting ready

How to do it…

How it works…

See also

Converting speech to text using the Google Cloud Speech-to-Text API

Getting ready

How to do it…

How it works…

There's more…

See also

Identifying Semantic Similarities within Text

Technical requirements

Finding the cosine similarity of the text

Getting ready

How to do it...

How it works...

There's more...

See also

Finding the distance between text

Getting ready

How to do it...

How it works...

See also

Finding differences between plaintext instances

Getting ready

How to do it...

How it works...

There's more...

See also

Finding hyponyms and antonyms

Getting ready

How to do it...

How it works...

There's more...

See also

Common Text Processing and Generation Tasks

Technical requirements

Generating random numbers

Getting ready

How to do it…

How it works…

There's more…

See also

Spell-checking using the LanguageTool API

Getting ready

How to do it…

How it works…

See also

Checking grammar using the LanguageTool API

Getting ready

How to do it…

How it works…

See also

Summarizing text in a document

Getting ready

How to do it…

How it works…

There's more...

See also

Creating, inverting, and using dictionaries

Getting ready

How to do it…

How it works…

There's more…

See also

Extracting Data for Use in NLP Analysis

Technical requirements

Connecting to an HTML page

Getting ready

How to do it…

How it works…

There's more…

See also

Extracting text and metadata from an HTML page

Getting ready

How to do it…

How it works…

There's more…

See also

Extracting text from a PDF document

Getting ready

How to do it…

How it works…

There's more…

See also

Extracting metadata from a PDF document

Getting ready

How to do it…

How it works…

There's more…

See also

Extracting text from a Word document

Getting ready

How to do it…

How it works…

There's more…

See also

Extracting metadata from a Word document

Getting ready

How to do it…

How it works…

There's more…

See also

Extracting text from a spreadsheet

Getting ready

How to do it…

How it works…

There's more…

See also

Extracting metadata from a spreadsheet

Getting ready

How to do it…

How it works…

See also

Creating a Chatbot

Technical requirements

Creating a simple chatbot using AWS

Getting ready

How to do it…

How it works…

See also

Creating a bot using AWS Toolkit for Eclipse

Getting ready

How to do it…

How it works…

See also

Creating a Lambda function

Getting ready

How to do it…

How it works…

See also

Uploading the Lambda function

Getting ready

How to do it…

How it works…

See also

Executing a Lambda function from Eclipse

Getting ready

How to do it…

How it works…

See also

Installation and Configuration

Technical requirements

Getting ready to use the Google Cloud Platform

Getting ready

How to do it…

How it works…

See also

Configuring Eclipse to use the Google Cloud Platform

Getting ready

How to do it…

How it works…

See also

Getting ready to use Amazon Web Services

Getting ready

How to do it…

How it works…

See also

Configuring Eclipse to use Amazon Web Services

Getting ready

How to do it…

How it works…

See also

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