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.

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Large-Scale Machine Learning in the Earth Sciences

Large-Scale Machine Learning in the Earth Sciences

Forthcoming

Ashok N. Srivastava, Ramakrishna Nemani, Karsten Steinhaeuser
June 30, 2017

Large-scale machine learning, currently focused on the internet and/or social network analysis, could prove highly beneficial in the study of earth science, a broad multidisciplinary field of study that generates huge amounts of data. This comprehensive book is the first to tackle the subject of...

Data Science and Analytics with Python

Data Science and Analytics with Python

Forthcoming

Jesus Rogel-Salazar
May 16, 2017

The book 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 analytics using tools developed in Python, such as SciKit Learn, Pandas, Numpy, etc. The use of Python is of...

Data Mining with R: Learning with Case Studies, Second Edition

Data Mining with R: Learning with Case Studies, Second Edition

Luis Torgo
January 19, 2017

Data Mining with R: Learning with Case Studies, Second Edition uses practical examples to illustrate the power of R and data mining. Providing an extensive update to the best-selling first edition, this new edition is divided into two parts. The first part will feature introductory material,...

Data Mining: A Tutorial-Based Primer, Second Edition

Data Mining: A Tutorial-Based Primer, Second Edition

Richard J. Roiger
December 01, 2016

"Dr. Roiger does an excellent job of describing in step by step detail formulae involved in various data mining algorithms, along with illustrations. In addition, his tutorials in Weka software provide excellent grounding for students in comprehending the underpinnings of Machine Learning as...

Graph-Based Social Media Analysis

Graph-Based Social Media Analysis

Ioannis Pitas
December 22, 2015

Focused on the mathematical foundations of social media analysis, Graph-Based Social Media Analysis provides a comprehensive introduction to the use of graph analysis in the study of social and digital media. It addresses an important scientific and technological challenge, namely the confluence of...

Text Mining and Visualization: Case Studies Using Open-Source Tools

Text Mining and Visualization: Case Studies Using Open-Source Tools

Markus Hofmann, Andrew Chisholm
December 18, 2015

Text Mining and Visualization: Case Studies Using Open-Source Tools provides an introduction to text mining using some of the most popular and powerful open-source tools: KNIME, RapidMiner, Weka, R, and Python. The contributors—all highly experienced with text mining and open-source...

Event Mining: Algorithms and Applications

Event Mining: Algorithms and Applications

Tao Li
October 20, 2015

Event mining encompasses techniques for automatically and efficiently extracting valuable knowledge from historical event/log data. The field, therefore, plays an important role in data-driven system management. Event Mining: Algorithms and Applications presents state-of-the-art event mining...

Accelerating Discovery: Mining Unstructured Information for Hypothesis Generation

Accelerating Discovery: Mining Unstructured Information for Hypothesis Generation

Scott Spangler
October 09, 2015

Unstructured Mining Approaches to Solve Complex Scientific Problems As the volume of scientific data and literature increases exponentially, scientists need more powerful tools and methods to process and synthesize information and to formulate new hypotheses that are most likely to be both true...

Healthcare Data Analytics

Healthcare Data Analytics

Chandan K. Reddy, Charu C. Aggarwal
June 23, 2015

At the intersection of computer science and healthcare, data analytics has emerged as a promising tool for solving problems across many healthcare-related disciplines. Supplying a comprehensive overview of recent healthcare analytics research, Healthcare Data Analytics provides a clear...

Data Classification: Algorithms and Applications

Data Classification: Algorithms and Applications

Charu C. Aggarwal
July 25, 2014

Comprehensive Coverage of the Entire Area of ClassificationResearch on the problem of classification tends to be fragmented across such areas as pattern recognition, database, data mining, and machine learning. Addressing the work of these different communities in a unified way, Data Classification...

Computational Business Analytics

Computational Business Analytics

Subrata Das
December 14, 2013

Learn How to Properly Use the Latest Analytics Approaches in Your Organization Computational Business Analytics presents tools and techniques for descriptive, predictive, and prescriptive analytics applicable across multiple domains. Through many examples and challenging case studies from a variety...

RapidMiner: Data Mining Use Cases and Business Analytics Applications

RapidMiner: Data Mining Use Cases and Business Analytics Applications

Markus Hofmann, Ralf Klinkenberg
October 25, 2013

Powerful, Flexible Tools for a Data-Driven WorldAs the data deluge continues in today’s world, the need to master data mining, predictive analytics, and business analytics has never been greater. These techniques and tools provide unprecedented insights into data, enabling better decision making...

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