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Python Web Scraping Cookbook

You're reading from   Python Web Scraping Cookbook Over 90 proven recipes to get you scraping with Python, microservices, Docker, and AWS

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Product type Paperback
Published in Feb 2018
Publisher Packt
ISBN-13 9781787285217
Length 364 pages
Edition 1st Edition
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Author (1):
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Michael Heydt Michael Heydt
Author Profile Icon Michael Heydt
Michael Heydt
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Table of Contents (13) Chapters Close

Preface 1. Getting Started with Scraping FREE CHAPTER 2. Data Acquisition and Extraction 3. Processing Data 4. Working with Images, Audio, and other Assets 5. Scraping - Code of Conduct 6. Scraping Challenges and Solutions 7. Text Wrangling and Analysis 8. Searching, Mining and Visualizing Data 9. Creating a Simple Data API 10. Creating Scraper Microservices with Docker 11. Making the Scraper as a Service Real 12. Other Books You May Enjoy

Performing lemmatization

Lemmatization is a more methodical process of converting words to their base. Where stemming generally just chops off the ends of words, lemmatization takes into account the morphological analysis of words, evaluating the context and part of speech to determine the inflected form, and makes a decision between different rules to determine the root.

How to do it

Lemmatization can be utilized in NTLK using the WordNetLemmatizer. This class uses the WordNet service, an online semantic database to make its decisions. The code in the 07/04_lemmatization.py file extends the previous stemming example to also calculate the lemmatization of each word. The code of importance is the following:

from nltk.stem...
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