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Machine Learning Paradigms

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Cover of 'Machine Learning Paradigms'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 Review of Previous Work Related to Recommender Systems
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    Chapter 3 The Learning Problem
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    Chapter 4 Content Description of Multimedia Data
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    Chapter 5 Similarity Measures for Recommendations Based on Objective Feature Subset Selection
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    Chapter 6 Cascade Recommendation Methods
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    Chapter 7 Evaluation of Cascade Recommendation Methods
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    Chapter 8 Conclusions and Future Work
Attention for Chapter 5: Similarity Measures for Recommendations Based on Objective Feature Subset Selection
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Chapter title
Similarity Measures for Recommendations Based on Objective Feature Subset Selection
Chapter number 5
Book title
Machine Learning Paradigms
Published by
Springer, Cham, January 2015
DOI 10.1007/978-3-319-19135-5_5
Book ISBNs
978-3-31-919134-8, 978-3-31-919135-5
Authors

Aristomenis S. Lampropoulos, George A. Tsihrintzis

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