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Clojure Data Analysis Cookbook - Second Edition

You're reading from   Clojure Data Analysis Cookbook - Second Edition Dive into data analysis with Clojure through over 100 practical recipes for every stage of the analysis and collection process

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Product type Paperback
Published in Jan 2015
Publisher
ISBN-13 9781784390297
Length 372 pages
Edition 2nd Edition
Languages
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Author (1):
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Eric Richard Rochester Eric Richard Rochester
Author Profile Icon Eric Richard Rochester
Eric Richard Rochester
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Toc

Table of Contents (14) Chapters Close

Preface 1. Importing Data for Analysis FREE CHAPTER 2. Cleaning and Validating Data 3. Managing Complexity with Concurrent Programming 4. Improving Performance with Parallel Programming 5. Distributed Data Processing with Cascalog 6. Working with Incanter Datasets 7. Statistical Data Analysis with Incanter 8. Working with Mathematica and R 9. Clustering, Classifying, and Working with Weka 10. Working with Unstructured and Textual Data 11. Graphing in Incanter 12. Creating Charts for the Web Index

Finding people, places, and things with Named Entity Recognition

One thing that's fairly easy to pull out of documents is named items. This includes things such as people's names, organizations, locations, and dates. These algorithms are called Named Entity Recognition (NER), and while they are not perfect, they're generally pretty good. Error rates under 0.1 are normal.

The OpenNLP library has classes to perform NER, and depending on what you train them with, they will identify people, locations, dates, or a number of other things. The clojure-opennlp library also exposes these classes in a good, Clojure-friendly way.

Getting ready

We'll continue building on the previous recipes in this chapter. Because of this, we'll use the same project.clj file:

(defproject com.ericrochester/text-data "0.1.0-SNAPSHOT"
  :dependencies [[org.clojure/clojure "1.6.0"]
                 [clojure-opennlp "0.3.2"]])

From the Tokenizing text recipe, we'll...

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