Recent Applications In Data Clustering
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Recent Applications in Data Clustering
Author | : Harun Pirim |
Publsiher | : BoD – Books on Demand |
Total Pages | : 250 |
Release | : 2018-08-01 |
Genre | : Computers |
ISBN | : 9781789235265 |
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Clustering has emerged as one of the more fertile fields within data analytics, widely adopted by companies, research institutions, and educational entities as a tool to describe similar/different groups. The book Recent Applications in Data Clustering aims to provide an outlook of recent contributions to the vast clustering literature that offers useful insights within the context of modern applications for professionals, academics, and students. The book spans the domains of clustering in image analysis, lexical analysis of texts, replacement of missing values in data, temporal clustering in smart cities, comparison of artificial neural network variations, graph theoretical approaches, spectral clustering, multiview clustering, and model-based clustering in an R package. Applications of image, text, face recognition, speech (synthetic and simulated), and smart city datasets are presented.
Data Clustering Theory Algorithms and Applications Second Edition
Author | : Guojun Gan,Chaoqun Ma,Jianhong Wu |
Publsiher | : SIAM |
Total Pages | : 430 |
Release | : 2020-11-10 |
Genre | : Mathematics |
ISBN | : 9781611976335 |
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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, covers the basics of data clustering, includes a list of popular clustering algorithms, and provides program code that helps users implement clustering algorithms. Data Clustering: Theory, Algorithms and Applications, Second Edition will be of interest to researchers, practitioners, and data scientists as well as undergraduate and graduate students.
Data Clustering
Author | : Charu C. Aggarwal,Chandan K. Reddy |
Publsiher | : CRC Press |
Total Pages | : 652 |
Release | : 2018-09-03 |
Genre | : Business & Economics |
ISBN | : 9781315362786 |
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Research on the problem of clustering tends to be fragmented across the pattern recognition, database, data mining, and machine learning communities. Addressing this problem in a unified way, Data Clustering: Algorithms and Applications provides complete coverage of the entire area of clustering, from basic methods to more refined and complex data clustering approaches. It pays special attention to recent issues in graphs, social networks, and other domains. The book focuses on three primary aspects of data clustering: Methods, describing key techniques commonly used for clustering, such as feature selection, agglomerative clustering, partitional clustering, density-based clustering, probabilistic clustering, grid-based clustering, spectral clustering, and nonnegative matrix factorization Domains, covering methods used for different domains of data, such as categorical data, text data, multimedia data, graph data, biological data, stream data, uncertain data, time series clustering, high-dimensional clustering, and big data Variations and Insights, discussing important variations of the clustering process, such as semisupervised clustering, interactive clustering, multiview clustering, cluster ensembles, and cluster validation In this book, top researchers from around the world explore the characteristics of clustering problems in a variety of application areas. They also explain how to glean detailed insight from the clustering process—including how to verify the quality of the underlying clusters—through supervision, human intervention, or the automated generation of alternative clusters.
Recent Applications in Data Clustering
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Author | : Harun Pirim |
Publsiher | : Unknown |
Total Pages | : 248 |
Release | : 2018 |
Genre | : Electronic computers. Computer science |
ISBN | : 1789235278 |
Download Recent Applications in Data Clustering Book in PDF, Epub and Kindle
Clustering has emerged as one of the more fertile fields within data analytics, widely adopted by companies, research institutions, and educational entities as a tool to describe similar/different groups. The book Recent Applications in Data Clustering aims to provide an outlook of recent contributions to the vast clustering literature that offers useful insights within the context of modern applications for professionals, academics, and students. The book spans the domains of clustering in image analysis, lexical analysis of texts, replacement of missing values in data, temporal clustering in smart cities, comparison of artificial neural network variations, graph theoretical approaches, spectral clustering, multiview clustering, and model-based clustering in an R package. Applications of image, text, face recognition, speech (synthetic and simulated), and smart city datasets are presented.
Classification Clustering and Data Analysis
Author | : Krzystof Jajuga,Andrzej Sokolowski,Hans-Hermann Bock |
Publsiher | : Springer Science & Business Media |
Total Pages | : 468 |
Release | : 2012-12-06 |
Genre | : Computers |
ISBN | : 9783642561818 |
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The book presents a long list of useful methods for classification, clustering and data analysis. By combining theoretical aspects with practical problems, it is designed for researchers as well as for applied statisticians and will support the fast transfer of new methodological advances to a wide range of applications.
Grouping Multidimensional Data
Author | : Jacob Kogan,Charles Nicholas |
Publsiher | : Taylor & Francis |
Total Pages | : 296 |
Release | : 2006-02-10 |
Genre | : Computers |
ISBN | : 354028348X |
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Publisher description
Classification Clustering and Data Mining Applications
Author | : International Federation of Classification Societies. Conference |
Publsiher | : Springer Science & Business Media |
Total Pages | : 676 |
Release | : 2004-06-09 |
Genre | : Computers |
ISBN | : 9783540220145 |
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Modern data analysis stands at the interface of statistics, computer science, and discrete mathematics. This volume describes new methods in this area, with special emphasis on classification and cluster analysis. Those methods are applied to problems in information retrieval, phylogeny, medical diagnosis, microarrays, and other active research areas.
Evolutionary Data Clustering Algorithms and Applications
Author | : Ibrahim Aljarah,Hossam Faris,Seyedali Mirjalili |
Publsiher | : Springer Nature |
Total Pages | : 248 |
Release | : 2021-02-20 |
Genre | : Technology & Engineering |
ISBN | : 9789813341913 |
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This book provides an in-depth analysis of the current evolutionary clustering techniques. It discusses the most highly regarded methods for data clustering. The book provides literature reviews about single objective and multi-objective evolutionary clustering algorithms. In addition, the book provides a comprehensive review of the fitness functions and evaluation measures that are used in most of evolutionary clustering algorithms. Furthermore, it provides a conceptual analysis including definition, validation and quality measures, applications, and implementations for data clustering using classical and modern nature-inspired techniques. It features a range of proven and recent nature-inspired algorithms used to data clustering, including particle swarm optimization, ant colony optimization, grey wolf optimizer, salp swarm algorithm, multi-verse optimizer, Harris hawks optimization, beta-hill climbing optimization. The book also covers applications of evolutionary data clustering in diverse fields such as image segmentation, medical applications, and pavement infrastructure asset management.