View All Book Series

BOOK SERIES


Chapman & Hall/CRC Data Mining and Knowledge Discovery Series


About the Series

As the field of data mining and knowledge discovery continues to grow, the timely dissemination of emerging research has become increasingly important both in math and stats, as well as across a range of disciplines seeking to take advantage of the wealth of data made available through informatics. This series aims to capture new developments and applications in data mining and knowledge discovery, while summarizing the computational tools and techniques useful in data analysis. This series is being established to encourage the integration of mathematical, statistical, and computational methods and techniques through the publication of a broad range of textbooks, reference works, and handbooks. We are looking to include those single author and contributed works that will—

  • Provide introductory and advanced instructional and reference material for students and professionals in the mathematical, statistical, and computational sciences
  • Supply researchers with the latest discoveries and the resources they need to advance the field
  • Offer assistance to those interdisciplinary researchers and practitioners seeking to make use of data mining technology without advanced mathematical backgrounds

The inclusion of concrete examples and applications is highly encouraged. The scope of the series includes, but is not limited to, titles in the areas of data mining and knowledge discovery methods and applications, modeling, algorithms, theory and foundations, data and knowledge visualization, data mining systems and tools, and privacy and security issues. We are willing to consider other relevant topics that might be proposed by potential contributors.

44 Series Titles

Per Page
Sort

Display
Introduction to Computational Health Informatics

Introduction to Computational Health Informatics

1st Edition

Forthcoming

Arvind Kumar Bansal, Javed Iqbal Khan, S. Kaisar Alam
December 20, 2019

This class-tested textbook is designed for a semester-long graduate, or senior undergraduate course on Computational Health Informatics. The focus of the book is on computational techniques that are widely used in health data analysis and health informatics. It integrates computer science and...

Multimedia Data Mining: A Systematic Introduction to Concepts and Theory

Multimedia Data Mining: A Systematic Introduction to Concepts and Theory

1st Edition

Zhongfei Zhang, Ruofei Zhang
October 18, 2019

Collecting the latest developments in the field, Multimedia Data Mining: A Systematic Introduction to Concepts and Theory defines multimedia data mining, its theory, and its applications. Two of the most active researchers in multimedia data mining explore how this young area has rapidly developed...

Knowledge Discovery for Counterterrorism and Law Enforcement

Knowledge Discovery for Counterterrorism and Law Enforcement

1st Edition

David Skillicorn
September 19, 2019

Most of the research aimed at counterterrorism, fraud detection, or other forensic applications assumes that this is a specialized application domain for mainstream knowledge discovery. Unfortunately, knowledge discovery changes completely when the datasets being used have been manipulated in order...

Privacy-Aware Knowledge Discovery: Novel Applications and New Techniques

Privacy-Aware Knowledge Discovery: Novel Applications and New Techniques

1st Edition

Francesco Bonchi, Elena Ferrari
September 05, 2019

Covering research at the frontier of this field, Privacy-Aware Knowledge Discovery: Novel Applications and New Techniques presents state-of-the-art privacy-preserving data mining techniques for application domains, such as medicine and social networks, that face the increasing heterogeneity and...

Industrial Applications of Machine Learning

Industrial Applications of Machine Learning

1st Edition

Pedro Larrañaga, David Atienza, Javier Diaz-Rozo, Alberto Ogbechie, Carlos Esteban Puerto-Santana, Concha Bielza
December 10, 2018

Industrial Applications of Machine Learning shows how machine learning can be applied to address real-world problems in the fourth industrial revolution, and provides the required knowledge and tools to empower readers to build their own solutions based on theory and practice. The book introduces...

Human Capital Systems, Analytics, and Data Mining

Human Capital Systems, Analytics, and Data Mining

1st Edition

Robert C. Hughes
August 22, 2018

Human Capital Systems, Analytics, and Data Mining provides human capital professionals, researchers, and students with a comprehensive and portable guide to human capital systems, analytics and data mining. The main purpose of this book is to provide a rich tool set of methods and tutorials for...

Exploratory Data Analysis Using R

Exploratory Data Analysis Using R

1st Edition

Ronald K. Pearson
May 29, 2018

Exploratory Data Analysis Using R provides a classroom-tested introduction to exploratory data analysis (EDA) and introduces the range of "interesting" – good, bad, and ugly – features that can be found in data, and why it is important to find them. It also introduces the mechanics of using R to...

Spectral Feature Selection for Data Mining

Spectral Feature Selection for Data Mining

1st Edition

Zheng Alan Zhao, Huan Liu
April 18, 2018

Spectral Feature Selection for Data Mining introduces a novel feature selection technique that establishes a general platform for studying existing feature selection algorithms and developing new algorithms for emerging problems in real-world applications. This technique represents a unified...

Feature Engineering for Machine Learning and Data Analytics

Feature Engineering for Machine Learning and Data Analytics

1st Edition

Guozhu Dong, Huan Liu
April 04, 2018

Feature engineering plays a vital role in big data analytics. Machine learning and data mining algorithms cannot work without data. Little can be achieved if there are few features to represent the underlying data objects, and the quality of results of those algorithms largely depends on the...

Data Science and Analytics with Python

Data Science and Analytics with Python

1st Edition

Jesus Rogel-Salazar
August 16, 2017

Data Science and Analytics with Python is designed for practitioners in data science and data analytics in both academic and business environments. The aim is to present the reader with the main concepts used in data science using tools developed in Python, such as SciKit-learn, Pandas, Numpy, and...

Large-Scale Machine Learning in the Earth Sciences

Large-Scale Machine Learning in the Earth Sciences

1st Edition

Ashok N. Srivastava, Ramakrishna Nemani, Karsten Steinhaeuser
August 07, 2017

From the Foreword: "While large-scale machine learning and data mining have greatly impacted a range of commercial applications, their use in the field of Earth sciences is still in the early stages. This book, edited by Ashok Srivastava, Ramakrishna Nemani, and Karsten Steinhaeuser, serves as an...

Social Networks with Rich Edge Semantics (Open Access)

Social Networks with Rich Edge Semantics (Open Access)

1st Edition

Quan Zheng, David Skillicorn
August 01, 2017

Social Networks with Rich Edge Semantics introduces a new mechanism for representing social networks in which pairwise relationships can be drawn from a range of realistic possibilities, including different types of relationships, different strengths in the directions of a pair, positive and...

AJAX loader