Book Image

Java Data Analysis

By : John R. Hubbard
Book Image

Java Data Analysis

By: John R. Hubbard

Overview of this book

Data analysis is a process of inspecting, cleansing, transforming, and modeling data with the aim of discovering useful information. Java is one of the most popular languages to perform your data analysis tasks. This book will help you learn the tools and techniques in Java to conduct data analysis without any hassle. After getting a quick overview of what data science is and the steps involved in the process, you’ll learn the statistical data analysis techniques and implement them using the popular Java APIs and libraries. Through practical examples, you will also learn the machine learning concepts such as classification and regression. In the process, you’ll familiarize yourself with tools such as Rapidminer and WEKA and see how these Java-based tools can be used effectively for analysis. You will also learn how to analyze text and other types of multimedia. Learn to work with relational, NoSQL, and time-series data. This book will also show you how you can utilize different Java-based libraries to create insightful and easy to understand plots and graphs. By the end of this book, you will have a solid understanding of the various data analysis techniques, and how to implement them using Java.
Table of Contents (20 chapters)
Java Data Analysis
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
Index

Chapter 9. Recommender Systems

Most online shoppers are probably familiar with Amazon's recommender system:

Figure 9.1: Amazon.com recommendations

When a customer views one item, the website displays a list of similar items that have sold well. That comes from their recommender system accessing Amazon's (amazing) database of products, customers, and sales.

Online recommender systems are now run by many vendors of goods and services: Netflix recommending movies, Apple recommending music, Audible recommending books, Yelp recommending restaurants, and so on.

A recommender system is an algorithm that predicts a customer's preferences for products based upon an analysis of that customer's previous choices compared to those of many other customers. These algorithms were pioneered by Amazon and Netflix, and are now widely used on the web.

Clustering algorithms provide one mechanism for building a recommender system: recommend what the other data points in the same cluster do. More specifically, we...