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Algorithms and Applications: Chapman & Hall/CRC Data Mining and Knowledge Discovery Series

Nathaniel Powell

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Published in Event Mining: Algorithms And Applications (Chapman Hall/CRC Data Mining And Knowledge Discovery 38)

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Algorithms and Applications is a book series that publishes high-quality monographs and textbooks on topics related to data mining and knowledge discovery. The series covers a wide range of topics, including:

Event Mining: Algorithms and Applications (Chapman Hall/CRC Data Mining and Knowledge Discovery 38)

Event Mining: Algorithms and Applications (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series Book 38)

by Giovanni Boccaccio

5 out of 5

Language	:	English
File size	:	21295 KB
Screen Reader	:	Supported
Print length	:	332 pages

* Data mining algorithms * Knowledge discovery techniques * Machine learning methods * Pattern recognition systems * Data mining applications

The books in the series are written by leading researchers in the field of data mining and knowledge discovery. They are written for researchers, practitioners, and students who are interested in learning about the latest advances in this field.

About the Series

The Chapman & Hall/CRC Data Mining and Knowledge Discovery Series is a leading book series in the field of data mining and knowledge discovery. The series publishes high-quality monographs and textbooks that cover a wide range of topics in the field. The books in the series are written by leading researchers in the field and are designed to provide readers with a comprehensive overview of the latest advances in data mining and knowledge discovery.

The series is edited by Jiawei Han, a leading researcher in the field of data mining. Han is a professor of computer science at the University of Illinois at Urbana-Champaign and the director of the Data Mining Research Center. He is the author of several books on data mining, including the popular textbook "Data Mining: Concepts and Techniques".

Aims and Scope

The aim of the series is to provide readers with a comprehensive overview of the latest advances in data mining and knowledge discovery. The series publishes books that cover a wide range of topics in the field, including:

* Data mining algorithms * Knowledge discovery techniques * Machine learning methods * Pattern recognition systems * Data mining applications

The books in the series are written by leading researchers in the field and are designed to provide readers with a comprehensive overview of the latest advances in data mining and knowledge discovery.

Target Audience

The series is intended for researchers, practitioners, and students who are interested in learning about the latest advances in data mining and knowledge discovery. The books in the series are written in a clear and concise style and are accessible to readers with a variety of backgrounds.

Editorial Board

The editorial board of the series consists of leading researchers in the field of data mining and knowledge discovery. The board members are responsible for selecting the books that are published in the series and for ensuring that the books meet the high standards of the series.

The editorial board includes the following members:

* Jiawei Han, University of Illinois at Urbana-Champaign * Micheline Kamber, University of California, Los Angeles * Jian Pei, Simon Fraser University * Philip S. Yu, University of Illinois at Chicago

Submission Guidelines

The series welcomes submissions of high-quality monographs and textbooks on topics related to data mining and knowledge discovery. Submissions should be in English and should be between 100 and 200 pages in length. Submissions should be submitted to the series editor, Jiawei Han, at [email protected].