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Most of the research aimed at counterterrorism, fraud detection, or other forensic applications assumes that this is a specialized application domain ...Savoir plus
Social Networks with Rich Edge Semantics introduces a new mechanism for representing social networks in which pairwise relationships can be drawn from...Savoir plus
Data Mining with R: Learning with Case Studies, Second Edition uses practical examples to illustrate the power of R and data mining. Providing an exte...Savoir plus
Focused on the mathematical foundations of social media analysis, Graph-Based Social Media Analysis provides a comprehensive introduction to the use o...Savoir plus
Feature engineering plays a vital role in big data analytics. Machine learning and data mining algorithms cannot work without data. Little can be achi...Savoir plus
Text Mining and Visualization: Case Studies Using Open-Source Tools provides an introduction to text mining using some of the most popular and powerfu...Savoir plus
Focused on the mathematical foundations of social media analysis, Graph-Based Social Media Analysis provides a comprehensive introduction to the use o...Savoir plus
Advanced Data Science and Analytics with Python enables data scientists to continue developing their skills and apply them in business as well as acad...Savoir plus
Identifying some of the most influential algorithms that are widely used in the data mining community, this volume provides a description of each algo...Savoir plus
Unstructured Mining Approaches to Solve Complex Scientific Problems As the volume of scientific data and literature increases exponentially, scientist...Savoir plus
Social Networks with Rich Edge Semantics introduces a new mechanism for representing social networks in which pairwise relationships can be drawn from...Savoir plus
Due to increasing demands for dimensionality reduction, research on feature selection has deeply and widely expanded into many fields, including compu...Savoir plus
Going beyond performing simple analyses, researchers involved in the highly dynamic field of computational intelligent data analysis design algorithms...Savoir plus
Data clustering is a highly interdisciplinary field, the goal of which is to divide a set of objects into homogeneous groups such that objects in the ...Savoir plus
Exploratory Data Analysis Using R provides a classroom-tested introduction to exploratory data analysis (EDA) and introduces the range of "interesting...Savoir plus
A Fruitful Field for Researching Data Mining Methodology and for Solving Real-Life Problems Contrast Data Mining: Concepts, Algorithms, and Applicatio...Savoir plus
Since the beginning of the Internet age and the increased use of ubiquitous computing devices, the large volume and continuous flow of distributed dat...Savoir plus
Statistical Data Mining Using SAS Applications, Second Edition describes statistical data mining concepts and demonstrates the features of user-friend...Savoir plus
Research on the problem of clustering tends to be fragmented across the pattern recognition, database, data mining, and machine learning communities. ...Savoir plus
Data Mining for Design and Marketing shows how to design and integrate data mining tools into human thinking processes in order to make better busines...Savoir plus
At the intersection of computer science and healthcare, data analytics has emerged as a promising tool for solving problems across many healthcare-rel...Savoir plus
Covering research at the frontier of this field, Privacy-Aware Knowledge Discovery: Novel Applications and New Techniques presents state-of-the-art pr...Savoir plus
Data Mining: A Tutorial-Based Primer, Second Edition provides a comprehensive introduction to data mining with a focus on model building and testing, ...Savoir plus
Event mining encompasses techniques for automatically and efficiently extracting valuable knowledge from historical event/log data. The field, therefo...Savoir plus