Book Image

Building a Recommendation System with R

Book Image

Building a Recommendation System with R

Overview of this book

Table of Contents (13 chapters)
Building a Recommendation System with R
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Preface
References
Index

Understanding recommender systems


Have you ever given a thought to the "People you may know" feature in LinkedIn or Facebook? This feature recommends a list of people whom you might know, who are similar to you based on your friends, friends of friends in your close circle, geographical location, skillsets, groups, liked pages, and so on. These recommendations are specific to you and differ from user to user.

Recommender systems are the software tools and techniques that provide suggestions, such as useful products on e-commerce websites, videos on YouTube, friends' recommendations on Facebook, book recommendations on Amazon, news recommendations on online news websites, and the list goes on.

The main goal of recommender systems is to provide suggestions to online users to make better decisions from many alternatives available over the Web. A better recommender system is directed more towards personalized recommendations by taking into consideration the available digital footprint of the user and information about a product, such as specifications, feedback from the users, comparison with other products, and so on, before making recommendations.