Chapman & Hall/CRC Data Mining and Knowledge Discovery Series
About the Book 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.
Data Science and Machine Learning for Non-Programmers: Using SAS Enterprise Miner
1st Edition
By Dothang Truong
January 01, 2026
As data continues to grow exponentially, knowledge of data science and machine learning has become more crucial than ever. Machine learning has grown exponentially; however, the abundance of resources can be overwhelming, making it challenging for new learners. This book aims to address this ...
Demystifying AI: Data Science and Machine Learning Using IBM SPSS Modeler
1st Edition
By Dothang Truong
December 16, 2025
As artificial intelligence advances at an exponential pace, understanding data science and machine learning has become increasingly essential. Yet, the wide range of available resources can be daunting, posing challenges for beginners. This second book builds on the foundation laid in the first, ...
Data Science and Analytics with Python
2nd Edition
By Jesus Rogel-Salazar
June 02, 2025
Since the first edition of “Data Science and Analytics with Python” we have witnessed an unprecedented explosion in the interest and development within the fields of Artificial Intelligence and Machine Learning. This surge has led to the widespread adoption of the book, not just among business ...
Knowledge Guided Machine Learning: Accelerating Discovery using Scientific Knowledge and Data
1st Edition
Edited
By Anuj Karpatne, Ramakrishnan Kannan, Vipin Kumar
August 26, 2024
Given their tremendous success in commercial applications, machine learning (ML) models are increasingly being considered as alternatives to science-based models in many disciplines. Yet, these "black-box" ML models have found limited success due to their inability to work well in the presence of ...
Automated Data Analysis Using Excel
2nd Edition
By Brian D. Bissett
August 19, 2020
This new edition covers some of the key topics relating to the latest version of MS Office through Excel 2019, including the creation of custom ribbons by injecting XML code into Excel Workbooks and how to link Excel VBA macros to customize ribbon objects. It now also provides examples in using ...
Advanced Data Science and Analytics with Python
1st Edition
By Jesus Rogel-Salazar
May 05, 2020
Advanced Data Science and Analytics with Python enables data scientists to continue developing their skills and apply them in business as well as academic settings. The subjects discussed in this book are complementary and a follow-up to the topics discussed in Data Science and Analytics with ...
Introduction to Computational Health Informatics
1st Edition
By Arvind Kumar Bansal, Javed Iqbal Khan, S. Kaisar Alam
January 14, 2020
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 and it integrates computer science and ...
Multimedia Data Mining: A Systematic Introduction to Concepts and Theory
1st Edition
By 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
1st Edition
By 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
1st Edition
Edited
By 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 ...
Spectral Feature Selection for Data Mining
1st Edition
By 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 ...
Mining Software Specifications: Methodologies and Applications
1st Edition
Edited
By David Lo, Siau-Cheng Khoo, Jiawei Han, Chao Liu
June 14, 2017
An emerging topic in software engineering and data mining, specification mining tackles software maintenance and reliability issues that cost economies billions of dollars each year. The first unified reference on the subject, Mining Software Specifications: Methodologies and Applications describes...