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  • Book Overview & Buying Natural Language Processing with Java
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Natural Language Processing with Java

Natural Language Processing with Java

By : Richard M. Reese , Richard M Reese
4.6 (7)
Buy this Book
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Natural Language Processing with Java

Natural Language Processing with Java

4.6 (7)
By: Richard M. Reese , Richard M Reese
Buy this Book

Overview of this book

If you are a Java programmer who wants to learn about the fundamental tasks underlying natural language processing, this book is for you. You will be able to identify and use NLP tasks for many common problems, and integrate them in your applications to solve more difficult problems. Readers should be familiar/experienced with Java software development.
Table of Contents (10 chapters)
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Preface
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Preface
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What this book covers
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What you need for this book
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Who this book is for
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Conventions
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Reader feedback
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Customer support
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1
1. Introduction to NLP
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1. Introduction to NLP
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What is NLP?
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Why use NLP?
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Why is NLP so hard?
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Survey of NLP tools
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Overview of text processing tasks
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Understanding NLP models
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Preparing data
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Summary
2
2. Finding Parts of Text
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2. Finding Parts of Text
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Understanding the parts of text
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What is tokenization?
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Simple Java tokenizers
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NLP tokenizer APIs
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Understanding normalization
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Summary
3
3. Finding Sentences
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3. Finding Sentences
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The SBD process
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What makes SBD difficult?
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Understanding SBD rules of LingPipe's HeuristicSentenceModel class
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Simple Java SBDs
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Using NLP APIs
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Training a Sentence Detector model
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Summary
4
4. Finding People and Things
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4. Finding People and Things
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Why NER is difficult?
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Techniques for name recognition
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Using regular expressions for NER
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Using NLP APIs
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Training a model
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Summary
5
5. Detecting Part of Speech
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5. Detecting Part of Speech
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The tagging process
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Using the NLP APIs
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Summary
6
6. Classifying Texts and Documents
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6. Classifying Texts and Documents
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How classification is used
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Understanding sentiment analysis
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Text classifying techniques
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Using APIs to classify text
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Summary
7
7. Using Parser to Extract Relationships
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7. Using Parser to Extract Relationships
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Relationship types
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Understanding parse trees
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Using extracted relationships
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Extracting relationships
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Using NLP APIs
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Extracting relationships for a question-answer system
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Summary
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8. Combined Approaches
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8. Combined Approaches
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Preparing data
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Pipelines
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Creating a pipeline to search text
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Summary
9
Index
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Index

Understanding the parts of text

There are a number of ways of categorizing parts of text. For example, we may be concerned with character-level issues such as punctuations with a possible need to ignore or expand contractions. At the word level, we may need to perform different operations such as:

  • Identifying morphemes using stemming and/or lemmatization

  • Expanding abbreviations and acronyms

  • Isolating number units

We cannot always split words with punctuations because the punctuations are sometimes considered to be part of the word, such as the word "can't". We may also be concerned with grouping multiple words to form meaningful phrases. Sentence detection can also be a factor. We do not necessarily want to group words that cross sentence boundaries.

In this chapter, we are primarily concerned with the tokenization process and a few specialized techniques such as stemming. We will not attempt to show how they are used in other NLP tasks. Those efforts are reserved for later chapters.

CONTINUE READING
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Tech Concepts
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Programming languages
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Natural Language Processing with Java
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