Abstract

This comprehensive reference consists of 18 chapters from prominent researchers in the field. Each chapter is self-contained, and synthesizes one aspect of frequent pattern mining. An emphasis is placed on simplifying the content, so that students and practitioners can benefit from the book. Each chapter contains a survey describing key research on the topic, a case study and future directions. Key topics include: Pattern Growth Methods, Frequent Pattern Mining in Data Streams, Mining Graph Patterns, Big Data Frequent Pattern Mining, Algorithms for Data Clustering and more. Advanced-level students in computer science, researchers and practitioners from industry will find this book an invaluable reference.

Original languageEnglish (US)
PublisherSpringer International Publishing
Number of pages471
Volume9783319078212
ISBN (Electronic)9783319078212
ISBN (Print)3319078208, 9783319078205
DOIs
StatePublished - Jul 1 2014

Fingerprint

Students
Computer science
Industry
Big data

ASJC Scopus subject areas

  • Computer Science(all)

Cite this

Aggarwal, C. C., & Han, J. (2014). Frequent pattern mining. Springer International Publishing. https://doi.org/10.1007/978-3-319-07821-2

Frequent pattern mining. / Aggarwal, Charu C.; Han, Jiawei.

Springer International Publishing, 2014. 471 p.

Research output: Book/ReportBook

Aggarwal, CC & Han, J 2014, Frequent pattern mining. vol. 9783319078212, Springer International Publishing. https://doi.org/10.1007/978-3-319-07821-2
Aggarwal CC, Han J. Frequent pattern mining. Springer International Publishing, 2014. 471 p. https://doi.org/10.1007/978-3-319-07821-2
Aggarwal, Charu C. ; Han, Jiawei. / Frequent pattern mining. Springer International Publishing, 2014. 471 p.
@book{b7387d66fa274ced8dd4b9577faf28a1,
title = "Frequent pattern mining",
abstract = "This comprehensive reference consists of 18 chapters from prominent researchers in the field. Each chapter is self-contained, and synthesizes one aspect of frequent pattern mining. An emphasis is placed on simplifying the content, so that students and practitioners can benefit from the book. Each chapter contains a survey describing key research on the topic, a case study and future directions. Key topics include: Pattern Growth Methods, Frequent Pattern Mining in Data Streams, Mining Graph Patterns, Big Data Frequent Pattern Mining, Algorithms for Data Clustering and more. Advanced-level students in computer science, researchers and practitioners from industry will find this book an invaluable reference.",
author = "Aggarwal, {Charu C.} and Jiawei Han",
year = "2014",
month = "7",
day = "1",
doi = "10.1007/978-3-319-07821-2",
language = "English (US)",
isbn = "3319078208",
volume = "9783319078212",
publisher = "Springer International Publishing",

}

TY - BOOK

T1 - Frequent pattern mining

AU - Aggarwal, Charu C.

AU - Han, Jiawei

PY - 2014/7/1

Y1 - 2014/7/1

N2 - This comprehensive reference consists of 18 chapters from prominent researchers in the field. Each chapter is self-contained, and synthesizes one aspect of frequent pattern mining. An emphasis is placed on simplifying the content, so that students and practitioners can benefit from the book. Each chapter contains a survey describing key research on the topic, a case study and future directions. Key topics include: Pattern Growth Methods, Frequent Pattern Mining in Data Streams, Mining Graph Patterns, Big Data Frequent Pattern Mining, Algorithms for Data Clustering and more. Advanced-level students in computer science, researchers and practitioners from industry will find this book an invaluable reference.

AB - This comprehensive reference consists of 18 chapters from prominent researchers in the field. Each chapter is self-contained, and synthesizes one aspect of frequent pattern mining. An emphasis is placed on simplifying the content, so that students and practitioners can benefit from the book. Each chapter contains a survey describing key research on the topic, a case study and future directions. Key topics include: Pattern Growth Methods, Frequent Pattern Mining in Data Streams, Mining Graph Patterns, Big Data Frequent Pattern Mining, Algorithms for Data Clustering and more. Advanced-level students in computer science, researchers and practitioners from industry will find this book an invaluable reference.

UR - http://www.scopus.com/inward/record.url?scp=84930326957&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84930326957&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-07821-2

DO - 10.1007/978-3-319-07821-2

M3 - Book

SN - 3319078208

SN - 9783319078205

VL - 9783319078212

BT - Frequent pattern mining

PB - Springer International Publishing

ER -