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You're reading from  Python Web Scraping Cookbook

Product typeBook
Published inFeb 2018
Reading LevelBeginner
PublisherPackt
ISBN-139781787285217
Edition1st Edition
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Michael Heydt
Michael Heydt
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Michael Heydt

Michael Heydt is an independent consultant, programmer, educator, and trainer. He has a passion for learning and sharing his knowledge of new technologies. Michael has worked in multiple industry verticals, including media, finance, energy, and healthcare. Over the last decade, he worked extensively with web, cloud, and mobile technologies and managed user experiences, interface design, and data visualization for major consulting firms and their clients. Michael's current company, Seamless Thingies , focuses on IoT development and connecting everything with everything. Michael is the author of numerous articles, papers, and books, such as D3.js By Example, Instant Lucene. NET, Learning Pandas, and Mastering Pandas for Finance, all by Packt. Michael is also a frequent speaker at .NET user groups and various mobile, cloud, and IoT conferences and delivers webinars on advanced technologies.
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Performing stemming

Stemming is the process of cutting down a token to its stem. Technically, it is the process or reducing inflected (and sometimes derived) words to their word stem - the base root form of the word. As an example, the words fishing, fished, and fisher stem from the root word fish. This helps to reduce the set of words being processed into a smaller base set that is more easily processed.

The most common algorithm for stemming was created by Martin Porter, and NLTK provides an implementation of this algorithm in the PorterStemmer. NLTK also provides an implementation of a Snowball stemmer, which was also created by Porter, and designed to handle languages other than English. There is one more implementation provided by NLTK referred to as a Lancaster stemmer. The Lancaster stemmer is considered the most aggressive stemmer of the three.

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Python Web Scraping Cookbook
Published in: Feb 2018Publisher: PacktISBN-13: 9781787285217

Author (1)

author image
Michael Heydt

Michael Heydt is an independent consultant, programmer, educator, and trainer. He has a passion for learning and sharing his knowledge of new technologies. Michael has worked in multiple industry verticals, including media, finance, energy, and healthcare. Over the last decade, he worked extensively with web, cloud, and mobile technologies and managed user experiences, interface design, and data visualization for major consulting firms and their clients. Michael's current company, Seamless Thingies , focuses on IoT development and connecting everything with everything. Michael is the author of numerous articles, papers, and books, such as D3.js By Example, Instant Lucene. NET, Learning Pandas, and Mastering Pandas for Finance, all by Packt. Michael is also a frequent speaker at .NET user groups and various mobile, cloud, and IoT conferences and delivers webinars on advanced technologies.
Read more about Michael Heydt