# Book: Frequent Pattern Mining

Frequent pattern mining is one of the distinguished problems in data mining. Learn about methods, domains, and applications of frequent pattern mining in this comprehensive survey of the field.

BOOK: FREQUENT PATTERN MINING

Ed. Charu Aggarwal, and Jiawei Han, Springer, 2014

TABLE OF CONTENTS and INTRODUCTION: http://www.charuaggarwal.net/freqbook.pdf

Comprehensive Coverage in the form of surveys on the entire area of Frequent Pattern Mining

Frequent pattern mining is one of the problems which serves as one of the distinguishing problems of the data mining area, separate from statistics and machine learning. In fact, the early work in frequent pattern mining provided an important impetus to the establishment of a separate field of data mining. Since then, the problem and its solutions have matured, along with the subsequent study of a wide variety of data types. This comprehensive book studies the field of frequent pattern mining from several perspectives:

Methods: The book first describes common techniques used for frequent pattern mining, such as Apriori, TreeProjection, Vertical Methods, FP-growth etc. Methods for long pattern mining, interesting pattern mining, compression methods, negative pattern mining, and constraint-based mining are studied separately.

Domains: The book then examines specific methods used for data domains such as discrete sequences, spatiotemporal data, graph data and uncertain data. It also covers large data sets and data streams due to the recent importance of the big data paradigm.

Applications: The book concludes with several important applications. Two chapters are dedicated to clustering and classification. The final chapter of the book discusses a wide variety of applications of frequent pattern mining along with pointers to resources for the practitioner.

Features

The table of contents and the introduction may be found at http://www.charuaggarwal.net/freqbook.pdf

Ed. Charu Aggarwal, and Jiawei Han, Springer, 2014

TABLE OF CONTENTS and INTRODUCTION: http://www.charuaggarwal.net/freqbook.pdf

Comprehensive Coverage in the form of surveys on the entire area of Frequent Pattern Mining

Frequent pattern mining is one of the problems which serves as one of the distinguishing problems of the data mining area, separate from statistics and machine learning. In fact, the early work in frequent pattern mining provided an important impetus to the establishment of a separate field of data mining. Since then, the problem and its solutions have matured, along with the subsequent study of a wide variety of data types. This comprehensive book studies the field of frequent pattern mining from several perspectives:

Methods: The book first describes common techniques used for frequent pattern mining, such as Apriori, TreeProjection, Vertical Methods, FP-growth etc. Methods for long pattern mining, interesting pattern mining, compression methods, negative pattern mining, and constraint-based mining are studied separately.

Domains: The book then examines specific methods used for data domains such as discrete sequences, spatiotemporal data, graph data and uncertain data. It also covers large data sets and data streams due to the recent importance of the big data paradigm.

Applications: The book concludes with several important applications. Two chapters are dedicated to clustering and classification. The final chapter of the book discusses a wide variety of applications of frequent pattern mining along with pointers to resources for the practitioner.

Features

- Presents an overview of the core methods in frequent pattern mining
- Covers recent problem domains, such as graphs, spatiotemporal data, and uncertain data
- Covers the streaming and big data paradigm
- Discusses important applications in detail.

The table of contents and the introduction may be found at http://www.charuaggarwal.net/freqbook.pdf

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