Reader small image

You're reading from  R Machine Learning By Example

Product typeBook
Published inMar 2016
Reading LevelIntermediate
Publisher
ISBN-139781784390846
Edition1st Edition
Languages
Tools
Right arrow

Understanding recommendation systems


Every individual in unique, the way we do things is what defines us uniquely. We eat, walk, talk, and even shop in a very unique way. Since the focus of this chapter is e-commerce, we will focus mostly on our shopping behaviors. We will utilize each customer's unique behavior to provide a personalized shopping experience.

To accomplish the task of providing a personalized shopping experience, we need a system to understand and model our customers. Recommendation engines are the systems which learn about customer preferences, choices, and so on, to recommend new products which are closer to what the user might have purchased themselves, thus providing a personalized experience. The options presented by such systems would have a high probability of the customer purchasing them.

Let us try to formally define a recommendation system.

Recommendation systems (or recommender engines) are a class of information filtering systems which analyze the input data to predict...

lock icon
The rest of the page is locked
Previous PageNext Page
You have been reading a chapter from
R Machine Learning By Example
Published in: Mar 2016Publisher: ISBN-13: 9781784390846