Reader small image

You're reading from  Python 3 Text Processing with NLTK 3 Cookbook

Product typeBook
Published inAug 2014
Reading LevelBeginner
Publisher
ISBN-139781782167853
Edition1st Edition
Languages
Tools
Right arrow
Author (1)
Jacob Perkins
Jacob Perkins
author image
Jacob Perkins

Jacob Perkins is the cofounder and CTO of Weotta, a local search company. Weotta uses NLP and machine learning to create powerful and easy-to-use natural language search for what to do and where to go. He is the author of Python Text Processing with NLTK 2.0 Cookbook, Packt Publishing, and has contributed a chapter to the Bad Data Handbook, O'Reilly Media. He writes about NLTK, Python, and other technology topics at http://streamhacker.com. To demonstrate the capabilities of NLTK and natural language processing, he developed http://text-processing.com, which provides simple demos and NLP APIs for commercial use. He has contributed to various open source projects, including NLTK, and created NLTK-Trainer to simplify the process of training NLTK models. For more information, visit https://github.com/japerk/nltk-trainer.
Read more about Jacob Perkins

Right arrow

Removing repeating characters


In everyday language, people are often not strictly grammatical. They will write things such as I looooooove it in order to emphasize the word love. However, computers don't know that "looooooove" is a variation of "love" unless they are told. This recipe presents a method to remove these annoying repeating characters in order to end up with a proper English word.

Getting ready

As in the previous recipe, we will be making use of the re module, and more specifically, backreferences. A backreference is a way to refer to a previously matched group in a regular expression. This will allow us to match and remove repeating characters.

How to do it...

We will create a class that has the same form as the RegexpReplacer class from the previous recipe. It will have a replace() method that takes a single word and returns a more correct version of that word, with the dubious repeating characters removed. This code can be found in replacers.py in the book's code bundle and is...

lock icon
The rest of the page is locked
Previous PageNext Page
You have been reading a chapter from
Python 3 Text Processing with NLTK 3 Cookbook
Published in: Aug 2014Publisher: ISBN-13: 9781782167853

Author (1)

author image
Jacob Perkins

Jacob Perkins is the cofounder and CTO of Weotta, a local search company. Weotta uses NLP and machine learning to create powerful and easy-to-use natural language search for what to do and where to go. He is the author of Python Text Processing with NLTK 2.0 Cookbook, Packt Publishing, and has contributed a chapter to the Bad Data Handbook, O'Reilly Media. He writes about NLTK, Python, and other technology topics at http://streamhacker.com. To demonstrate the capabilities of NLTK and natural language processing, he developed http://text-processing.com, which provides simple demos and NLP APIs for commercial use. He has contributed to various open source projects, including NLTK, and created NLTK-Trainer to simplify the process of training NLTK models. For more information, visit https://github.com/japerk/nltk-trainer.
Read more about Jacob Perkins