Clustering Methods For Big Data Analytics

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Clustering Methods for Big Data Analytics

Author : Olfa Nasraoui
Publisher : Springer
ISBN 13 : 3319978640
Total Pages : 187 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Clustering Methods for Big Data Analytics by : Olfa Nasraoui

Download or read book Clustering Methods for Big Data Analytics written by Olfa Nasraoui and published by Springer. This book was released on 2018-10-27 with total page 187 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights the state of the art and recent advances in Big Data clustering methods and their innovative applications in contemporary AI-driven systems. The book chapters discuss Deep Learning for Clustering, Blockchain data clustering, Cybersecurity applications such as insider threat detection, scalable distributed clustering methods for massive volumes of data; clustering Big Data Streams such as streams generated by the confluence of Internet of Things, digital and mobile health, human-robot interaction, and social networks; Spark-based Big Data clustering using Particle Swarm Optimization; and Tensor-based clustering for Web graphs, sensor streams, and social networks. The chapters in the book include a balanced coverage of big data clustering theory, methods, tools, frameworks, applications, representation, visualization, and clustering validation.

Computational Science and Its Applications - ICCSA 2014

Author : Beniamino Murgante
Publisher : Springer
ISBN 13 : 3319091565
Total Pages : 808 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Computational Science and Its Applications - ICCSA 2014 by : Beniamino Murgante

Download or read book Computational Science and Its Applications - ICCSA 2014 written by Beniamino Murgante and published by Springer. This book was released on 2014-07-02 with total page 808 pages. Available in PDF, EPUB and Kindle. Book excerpt: The six-volume set LNCS 8579-8584 constitutes the refereed proceedings of the 14th International Conference on Computational Science and Its Applications, ICCSA 2014, held in Guimarães, Portugal, in June/July 2014. The 347 revised papers presented in 30 workshops and a special track were carefully reviewed and selected from 1167. The 289 papers presented in the workshops cover various areas in computational science ranging from computational science technologies to specific areas of computational science such as computational geometry and security.

Data Clustering

Author : Charu C. Aggarwal
Publisher : CRC Press
ISBN 13 : 1466558210
Total Pages : 654 pages
Book Rating : 4.4/5 (665 download)

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Book Synopsis Data Clustering by : Charu C. Aggarwal

Download or read book Data Clustering written by Charu C. Aggarwal and published by CRC Press. This book was released on 2013-08-21 with total page 654 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Handbook of Research on Big Data Clustering and Machine Learning

Author : Garcia Marquez, Fausto Pedro
Publisher : IGI Global
ISBN 13 : 1799801071
Total Pages : 478 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Handbook of Research on Big Data Clustering and Machine Learning by : Garcia Marquez, Fausto Pedro

Download or read book Handbook of Research on Big Data Clustering and Machine Learning written by Garcia Marquez, Fausto Pedro and published by IGI Global. This book was released on 2019-10-04 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: As organizations continue to develop, there is an increasing need for technological methods that can keep up with the rising amount of data and information that is being generated. Machine learning is a tool that has become powerful due to its ability to analyze large amounts of data quickly. Machine learning is one of many technological advancements that is being implemented into a multitude of specialized fields. An extensive study on the execution of these advancements within professional industries is necessary. The Handbook of Research on Big Data Clustering and Machine Learning is an essential reference source that synthesizes the analytic principles of clustering and machine learning to big data and provides an interface between the main disciplines of engineering/technology and the organizational, administrative, and planning abilities of management. Featuring research on topics such as project management, contextual data modeling, and business information systems, this book is ideally designed for engineers, economists, finance officers, marketers, decision makers, business professionals, industry practitioners, academicians, students, and researchers seeking coverage on the implementation of big data and machine learning within specific professional fields.

Data Clustering: Theory, Algorithms, and Applications, Second Edition

Author : Guojun Gan
Publisher : SIAM
ISBN 13 : 1611976332
Total Pages : 430 pages
Book Rating : 4.6/5 (119 download)

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Book Synopsis Data Clustering: Theory, Algorithms, and Applications, Second Edition by : Guojun Gan

Download or read book Data Clustering: Theory, Algorithms, and Applications, Second Edition written by Guojun Gan and published by SIAM. This book was released on 2020-11-10 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Clustering Algorithms

Author : John A. Hartigan
Publisher : John Wiley & Sons
ISBN 13 :
Total Pages : 374 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Clustering Algorithms by : John A. Hartigan

Download or read book Clustering Algorithms written by John A. Hartigan and published by John Wiley & Sons. This book was released on 1975 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: Shows how Galileo, Newton, and Einstein tried to explain gravity. Discusses the concept of microgravity and NASA's research on gravity and microgravity.

Computational Intelligence for Big Data Analysis

Author : D.P. Acharjya
Publisher : Springer
ISBN 13 : 3319165984
Total Pages : 267 pages
Book Rating : 4.3/5 (191 download)

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Book Synopsis Computational Intelligence for Big Data Analysis by : D.P. Acharjya

Download or read book Computational Intelligence for Big Data Analysis written by D.P. Acharjya and published by Springer. This book was released on 2015-04-21 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: The work presented in this book is a combination of theoretical advancements of big data analysis, cloud computing, and their potential applications in scientific computing. The theoretical advancements are supported with illustrative examples and its applications in handling real life problems. The applications are mostly undertaken from real life situations. The book discusses major issues pertaining to big data analysis using computational intelligence techniques and some issues of cloud computing. An elaborate bibliography is provided at the end of each chapter. The material in this book includes concepts, figures, graphs, and tables to guide researchers in the area of big data analysis and cloud computing.

Data Science

Author : Francesco Palumbo
Publisher : Springer
ISBN 13 : 3319557238
Total Pages : 342 pages
Book Rating : 4.3/5 (195 download)

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Book Synopsis Data Science by : Francesco Palumbo

Download or read book Data Science written by Francesco Palumbo and published by Springer. This book was released on 2017-07-04 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited volume on the latest advances in data science covers a wide range of topics in the context of data analysis and classification. In particular, it includes contributions on classification methods for high-dimensional data, clustering methods, multivariate statistical methods, and various applications. The book gathers a selection of peer-reviewed contributions presented at the Fifteenth Conference of the International Federation of Classification Societies (IFCS2015), which was hosted by the Alma Mater Studiorum, University of Bologna, from July 5 to 8, 2015.

Model-Based Clustering and Classification for Data Science

Author : Charles Bouveyron
Publisher : Cambridge University Press
ISBN 13 : 1108640591
Total Pages : 447 pages
Book Rating : 4.1/5 (86 download)

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Book Synopsis Model-Based Clustering and Classification for Data Science by : Charles Bouveyron

Download or read book Model-Based Clustering and Classification for Data Science written by Charles Bouveyron and published by Cambridge University Press. This book was released on 2019-07-25 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cluster analysis finds groups in data automatically. Most methods have been heuristic and leave open such central questions as: how many clusters are there? Which method should I use? How should I handle outliers? Classification assigns new observations to groups given previously classified observations, and also has open questions about parameter tuning, robustness and uncertainty assessment. This book frames cluster analysis and classification in terms of statistical models, thus yielding principled estimation, testing and prediction methods, and sound answers to the central questions. It builds the basic ideas in an accessible but rigorous way, with extensive data examples and R code; describes modern approaches to high-dimensional data and networks; and explains such recent advances as Bayesian regularization, non-Gaussian model-based clustering, cluster merging, variable selection, semi-supervised and robust classification, clustering of functional data, text and images, and co-clustering. Written for advanced undergraduates in data science, as well as researchers and practitioners, it assumes basic knowledge of multivariate calculus, linear algebra, probability and statistics.

Big Data Analytics

Author : Saumyadipta Pyne
Publisher : Springer
ISBN 13 : 8132236289
Total Pages : 276 pages
Book Rating : 4.1/5 (322 download)

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Book Synopsis Big Data Analytics by : Saumyadipta Pyne

Download or read book Big Data Analytics written by Saumyadipta Pyne and published by Springer. This book was released on 2016-10-12 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book has a collection of articles written by Big Data experts to describe some of the cutting-edge methods and applications from their respective areas of interest, and provides the reader with a detailed overview of the field of Big Data Analytics as it is practiced today. The chapters cover technical aspects of key areas that generate and use Big Data such as management and finance; medicine and healthcare; genome, cytome and microbiome; graphs and networks; Internet of Things; Big Data standards; bench-marking of systems; and others. In addition to different applications, key algorithmic approaches such as graph partitioning, clustering and finite mixture modelling of high-dimensional data are also covered. The varied collection of themes in this volume introduces the reader to the richness of the emerging field of Big Data Analytics.

Big Data Analytics

Author : Arun K. Somani
Publisher : CRC Press
ISBN 13 : 1315391244
Total Pages : 484 pages
Book Rating : 4.3/5 (153 download)

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Book Synopsis Big Data Analytics by : Arun K. Somani

Download or read book Big Data Analytics written by Arun K. Somani and published by CRC Press. This book was released on 2017-10-30 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: The proposed book will discuss various aspects of big data Analytics. It will deliberate upon the tools, technology, applications, use cases and research directions in the field. Chapters would be contributed by researchers, scientist and practitioners from various reputed universities and organizations for the benefit of readers.

Mining Text Data

Author : Charu C. Aggarwal
Publisher : Springer Science & Business Media
ISBN 13 : 1461432235
Total Pages : 524 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Mining Text Data by : Charu C. Aggarwal

Download or read book Mining Text Data written by Charu C. Aggarwal and published by Springer Science & Business Media. This book was released on 2012-02-03 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt: Text mining applications have experienced tremendous advances because of web 2.0 and social networking applications. Recent advances in hardware and software technology have lead to a number of unique scenarios where text mining algorithms are learned. Mining Text Data introduces an important niche in the text analytics field, and is an edited volume contributed by leading international researchers and practitioners focused on social networks & data mining. This book contains a wide swath in topics across social networks & data mining. Each chapter contains a comprehensive survey including the key research content on the topic, and the future directions of research in the field. There is a special focus on Text Embedded with Heterogeneous and Multimedia Data which makes the mining process much more challenging. A number of methods have been designed such as transfer learning and cross-lingual mining for such cases. Mining Text Data simplifies the content, so that advanced-level students, practitioners and researchers in computer science can benefit from this book. Academic and corporate libraries, as well as ACM, IEEE, and Management Science focused on information security, electronic commerce, databases, data mining, machine learning, and statistics are the primary buyers for this reference book.

Big Data Analytics Methods

Author : Peter Ghavami
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 1547401583
Total Pages : 282 pages
Book Rating : 4.5/5 (474 download)

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Book Synopsis Big Data Analytics Methods by : Peter Ghavami

Download or read book Big Data Analytics Methods written by Peter Ghavami and published by Walter de Gruyter GmbH & Co KG. This book was released on 2019-12-16 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data Analytics Methods unveils secrets to advanced analytics techniques ranging from machine learning, random forest classifiers, predictive modeling, cluster analysis, natural language processing (NLP), Kalman filtering and ensembles of models for optimal accuracy of analysis and prediction. More than 100 analytics techniques and methods provide big data professionals, business intelligence professionals and citizen data scientists insight on how to overcome challenges and avoid common pitfalls and traps in data analytics. The book offers solutions and tips on handling missing data, noisy and dirty data, error reduction and boosting signal to reduce noise. It discusses data visualization, prediction, optimization, artificial intelligence, regression analysis, the Cox hazard model and many analytics using case examples with applications in the healthcare, transportation, retail, telecommunication, consulting, manufacturing, energy and financial services industries. This book's state of the art treatment of advanced data analytics methods and important best practices will help readers succeed in data analytics.

Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities

Author : Segall, Richard S.
Publisher : IGI Global
ISBN 13 : 1799827704
Total Pages : 237 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities by : Segall, Richard S.

Download or read book Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities written by Segall, Richard S. and published by IGI Global. This book was released on 2020-02-21 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the development of computing technologies in today’s modernized world, software packages have become easily accessible. Open source software, specifically, is a popular method for solving certain issues in the field of computer science. One key challenge is analyzing big data due to the high amounts that organizations are processing. Researchers and professionals need research on the foundations of open source software programs and how they can successfully analyze statistical data. Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities provides emerging research exploring the theoretical and practical aspects of cost-free software possibilities for applications within data analysis and statistics with a specific focus on R and Python. Featuring coverage on a broad range of topics such as cluster analysis, time series forecasting, and machine learning, this book is ideally designed for researchers, developers, practitioners, engineers, academicians, scholars, and students who want to more fully understand in a brief and concise format the realm and technologies of open source software for big data and how it has been used to solve large-scale research problems in a multitude of disciplines.

Big Data Analytics

Author : P. Krishna Reddy
Publisher : Springer
ISBN 13 : 3319724134
Total Pages : 316 pages
Book Rating : 4.3/5 (197 download)

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Book Synopsis Big Data Analytics by : P. Krishna Reddy

Download or read book Big Data Analytics written by P. Krishna Reddy and published by Springer. This book was released on 2017-12-04 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed conference proceedings of the 5th International Conference on Big Data Analytics, BDA 2017, held in Hyderabad, India, in December 2017. The 21 revised full papers were carefully reviewed and selected from 80 submissions and cover topics on big data analytics, information and knowledge management, mining of massive datasets, computational modeling, data mining and analysis.

Modern Algorithms of Cluster Analysis

Author : Slawomir Wierzchoń
Publisher : Springer
ISBN 13 : 3319693085
Total Pages : 421 pages
Book Rating : 4.3/5 (196 download)

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Book Synopsis Modern Algorithms of Cluster Analysis by : Slawomir Wierzchoń

Download or read book Modern Algorithms of Cluster Analysis written by Slawomir Wierzchoń and published by Springer. This book was released on 2017-12-29 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides the reader with a basic understanding of the formal concepts of the cluster, clustering, partition, cluster analysis etc. The book explains feature-based, graph-based and spectral clustering methods and discusses their formal similarities and differences. Understanding the related formal concepts is particularly vital in the epoch of Big Data; due to the volume and characteristics of the data, it is no longer feasible to predominantly rely on merely viewing the data when facing a clustering problem. Usually clustering involves choosing similar objects and grouping them together. To facilitate the choice of similarity measures for complex and big data, various measures of object similarity, based on quantitative (like numerical measurement results) and qualitative features (like text), as well as combinations of the two, are described, as well as graph-based similarity measures for (hyper) linked objects and measures for multilayered graphs. Numerous variants demonstrating how such similarity measures can be exploited when defining clustering cost functions are also presented. In addition, the book provides an overview of approaches to handling large collections of objects in a reasonable time. In particular, it addresses grid-based methods, sampling methods, parallelization via Map-Reduce, usage of tree-structures, random projections and various heuristic approaches, especially those used for community detection.

BIG DATA ANALYTICS

Author : Parag Kulkarni
Publisher : PHI Learning Pvt. Ltd.
ISBN 13 : 8120351169
Total Pages : 208 pages
Book Rating : 4.1/5 (23 download)

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Book Synopsis BIG DATA ANALYTICS by : Parag Kulkarni

Download or read book BIG DATA ANALYTICS written by Parag Kulkarni and published by PHI Learning Pvt. Ltd.. This book was released on 2016-07-07 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is an unstructured data mining quest, which takes the reader through different features of unstructured data mining while unfolding the practical facets of Big Data. It emphasizes more on machine learning and mining methods required for processing and decision-making. The text begins with the introduction to the subject and explores the concept of data mining methods and models along with the applications. It then goes into detail on other aspects of Big Data analytics, such as clustering, incremental learning, multi-label association and knowledge representation. The readers are also made familiar with business analytics to create value. The book finally ends with a discussion on the areas where research can be explored.