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Java Data Analysis

You're reading from   Java Data Analysis Data mining, big data analysis, NoSQL, and data visualization

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Product type Paperback
Published in Sep 2017
Publisher Packt
ISBN-13 9781787285651
Length 412 pages
Edition 1st Edition
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Concepts
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Author (1):
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John R. Hubbard John R. Hubbard
Author Profile Icon John R. Hubbard
John R. Hubbard
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Table of Contents (14) Chapters Close

Preface 1. Introduction to Data Analysis 2. Data Preprocessing FREE CHAPTER 3. Data Visualization 4. Statistics 5. Relational Databases 6. Regression Analysis 7. Classification Analysis 8. Cluster Analysis 9. Recommender Systems 10. NoSQL Databases 11. Big Data Analysis with Java A. Java Tools Index

Summary

In this chapter, we have described the general strategy of recommender systems and implemented in Java an early version developed at Amazon. We first explored the notion of similarity measures, including cosine similarity. We saw how user ratings are used in recommender systems. We looked at the general idea of sparse matrices, which is the likely mathematical structure for a utility matrix, and then saw how they could be implemented using a random access file. Finally, we reviewed the Netflix prize competition, which raised the level of interest in recommender systems among data scientists.

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