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Frequent Pattern Mining

Overview of attention for book
Cover of 'Frequent Pattern Mining'

Table of Contents

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    Book Overview
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    Chapter 1 An Introduction to Frequent Pattern Mining
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    Chapter 2 Frequent Pattern Mining Algorithms: A Survey
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    Chapter 3 Pattern-Growth Methods
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    Chapter 4 Mining Long Patterns
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    Chapter 5 Interesting Patterns
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    Chapter 6 Negative Association Rules
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    Chapter 7 Constraint-Based Pattern Mining
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    Chapter 8 Mining and Using Sets of Patterns through Compression
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    Chapter 9 Frequent Pattern Mining in Data Streams
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    Chapter 10 Big Data Frequent Pattern Mining
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    Chapter 11 Sequential Pattern Mining
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    Chapter 12 Spatiotemporal Pattern Mining: Algorithms and Applications
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    Chapter 13 Mining Graph Patterns
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    Chapter 14 Uncertain Frequent Pattern Mining
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    Chapter 15 Privacy Issues in Association Rule Mining
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    Chapter 16 Frequent Pattern Mining Algorithms for Data Clustering
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    Chapter 17 Supervised Pattern Mining and Applications to Classification
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    Chapter 18 Applications of Frequent Pattern Mining
Attention for Chapter 16: Frequent Pattern Mining Algorithms for Data Clustering
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Chapter title
Frequent Pattern Mining Algorithms for Data Clustering
Chapter number 16
Book title
Frequent Pattern Mining
Published by
Springer International Publishing, August 2014
DOI 10.1007/978-3-319-07821-2_16
Book ISBNs
978-3-31-907820-5, 978-3-31-907821-2
Authors

Arthur Zimek, Ira Assent, Jilles Vreeken

Editors

Charu C. Aggarwal, Jiawei Han

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 27%
Student > Ph. D. Student 4 27%
Student > Bachelor 2 13%
Student > Postgraduate 2 13%
Student > Doctoral Student 1 7%
Other 2 13%
Readers by discipline Count As %
Computer Science 11 73%
Engineering 2 13%
Economics, Econometrics and Finance 1 7%
Biochemistry, Genetics and Molecular Biology 1 7%

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