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Data clustering, also known as cluster analysis, is an unsupervised process that divides a set of objects into homogeneous groups. Since the publication of the first edition of this monograph in 2007, development in the area has exploded, especially in clustering algorithms for big data and open-source software for cluster analysis. This second edition reflects these new developments.
Data Clustering: Theory, Algorithms, and Applications, Second Edition:
Data clustering, also known as cluster analysis, is an unsupervised process that divides a set of objects into homogeneous groups. Since the publication of the first edition of this monograph in 2007, development in the area has exploded, especially in clustering algorithms for big data and open-source software for cluster analysis. This second edition reflects these new developments.
Data Clustering: Theory, Algorithms, and Applications, Second Edition:
Guojun Gan is an associate professor in the Department of
Mathematics at the University of Connecticut. Before moving to
academia, he worked at a life insurance company and at a hedge
fund. He is a Fellow of the Society of Actuaries and his research
interests fall within the interdisciplinary areas of actuarial
science and data science.
Chaoqun Ma is a professor of management science in the
College of Business Administration at Hunan University, where he
served as dean from 2009 to 2019. His research interests include
financial engineering, financial risk management, computational
management, resource and environmental management, system
optimization, and decision-making theory.
Jianhong Wu is a University Distinguished Research Professor
in the Department of Mathematics and Statistics, the founding
director of the Laboratory for Industrial and Applied Mathematics,
and a senior Canada Research Chair in Industrial and Applied
Mathematics at York University. He has received several prestigious
awards, including the Queen Elizabeth II Diamond Jubilee Medal from
the Government of Canada, and the CAIMS-Fields Industrial
Mathematics Prize. His research interests include nonlinear
dynamics, delay differential equations, neural networks, pattern
recognition, mathematical ecology, epidemiology, and big data
analytics.
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