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Machine Learning for the Web

You're reading from   Machine Learning for the Web Gaining insight and intelligence from the internet with Python

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Product type Paperback
Published in Jul 2016
Publisher Packt
ISBN-13 9781785886607
Length 298 pages
Edition 1st Edition
Languages
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Authors (2):
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Andrea Isoni Andrea Isoni
Author Profile Icon Andrea Isoni
Andrea Isoni
Steve Essinger Steve Essinger
Author Profile Icon Steve Essinger
Steve Essinger
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Toc

Table of Contents (10) Chapters Close

Preface 1. Introduction to Practical Machine Learning Using Python FREE CHAPTER 2. Unsupervised Machine Learning 3. Supervised Machine Learning 4. Web Mining Techniques 5. Recommendation Systems 6. Getting Started with Django 7. Movie Recommendation System Web Application 8. Sentiment Analyser Application for Movie Reviews Index

Chapter 4. Web Mining Techniques

Web data mining techniques are used to explore the data available online and then extract the relevant information from the Internet. Searching on the web is a complex process that requires different algorithms, and they will be the main focus of this chapter. Given a search query, the relevant pages are obtained using the data available on each web page, which is usually divided in the page content and the page hyperlinks to other pages. Usually, a search engine has multiple components:

  • A web crawler or spider for collecting web pages
  • A parser that extracts content and preprocesses web pages
  • An indexer to organize the web pages in data structures
  • A retrieval information system to score the most important documents related to a query
  • A ranking algorithm to order the web pages in a meaningful manner

These parts can be divided into web structure mining techniques and web content mining techniques.

The web crawler, indexer, and ranking procedures refer to...

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