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Mastering Text Mining with R

You're reading from  Mastering Text Mining with R

Product type Book
Published in Dec 2016
Publisher Packt
ISBN-13 9781783551811
Pages 258 pages
Edition 1st Edition
Languages
Concepts
Author (1):
KUMAR ASHISH KUMAR ASHISH
Profile icon KUMAR ASHISH

Feature extraction


Feature extraction is a very important and valuable step in text mining. A system that can extract features from text has potential to be used in lots of applications. The initial step for feature extraction would be tagging the document; this tagged document is then processed to extract the required entities that are meaningful.

The elements that can be extracted from the text are:

  • Entities: These are some of the pieces of meaningful information that can be found in the document, for example, location, companies, people, and so on

  • Attributes: These are the features of the extracted entities, for example the title of the person, type of organization, and so on

  • Events: These are the activities in which the entities participate, for example, dates

Textual Entailment Human communication is diverse in terms of the usage of different expressions to communicate the same message. This proves to be quite a challenging problem in natural language processing. Consider, for example...

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