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Mastering Text Mining with R

You're reading from   Mastering Text Mining with R Extract and recognize your text data

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Product type Paperback
Published in Dec 2016
Publisher Packt
ISBN-13 9781783551811
Length 258 pages
Edition 1st Edition
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Author (1):
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KUMAR ASHISH KUMAR ASHISH
Author Profile Icon KUMAR ASHISH
KUMAR ASHISH
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Toc

Entity extraction


The process of extracting information from unstructured documents is called information extraction. In today's world, most of the data produced over the internet is semi-structured or unstructured; this data is mostly in a human-understandable format, what we call natural language, so most of the time, natural language processing comes into play during information extraction. Entity recognition is a sub process in the chain of information extraction process. NER is one of the important and vital parts of the information extraction process. NER is sometimes also called entity extraction or entity chunking .The main job of NER is to extract the rigid designators in the document and classify these elements in the text to a predefined category. The named entity extractor has a set of predefined categories such as the following:

  • persons

  • organizations

  • locations

  • time

  • money

  • percentages

  • dates

Given an unstructured document, NER will annotate the block or extract the relevant features. Consider...

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