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Soft Computing for Data Mining Applications

Author: K. R. Venugopal

Publisher: Springer Science & Business Media

Published: 2009-03-11

Total Pages: 354

ISBN-13: 3642001920

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The authors have consolidated their research work in this volume titled Soft Computing for Data Mining Applications. The monograph gives an insight into the research in the ?elds of Data Mining in combination with Soft Computing methodologies. In these days, the data continues to grow - ponentially. Much of the data is implicitly or explicitly imprecise. Database discovery seeks to discover noteworthy, unrecognized associations between the data items in the existing database. The potential of discovery comes from the realization that alternate contexts may reveal additional valuable information. The rate at which the data is storedis growing at a phenomenal rate. Asaresult,traditionaladhocmixturesofstatisticaltechniquesanddata managementtools are no longer adequate for analyzing this vast collection of data. Severaldomainswherelargevolumesofdataarestoredincentralizedor distributeddatabasesincludesapplicationslikeinelectroniccommerce,bio- formatics, computer security, Web intelligence, intelligent learning database systems,?nance,marketing,healthcare,telecommunications,andother?elds. E?cient tools and algorithms for knowledge discovery in large data sets have been devised during the recent years. These methods exploit the ca- bility of computers to search huge amounts of data in a fast and e?ective manner. However,the data to be analyzed is imprecise and a?icted with - certainty. In the case of heterogeneous data sources such as text and video, the data might moreover be ambiguous and partly con?icting. Besides, p- terns and relationships of interest are usually approximate. Thus, in order to make the information mining process more robust it requires tolerance toward imprecision, uncertainty and exceptions.

Book Synopsis Soft Computing for Data Mining Applications by : K. R. Venugopal

Download or read book Soft Computing for Data Mining Applications written by K. R. Venugopal and published by Springer Science & Business Media. This book was released on 2009-03-11 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: The authors have consolidated their research work in this volume titled Soft Computing for Data Mining Applications. The monograph gives an insight into the research in the ?elds of Data Mining in combination with Soft Computing methodologies. In these days, the data continues to grow - ponentially. Much of the data is implicitly or explicitly imprecise. Database discovery seeks to discover noteworthy, unrecognized associations between the data items in the existing database. The potential of discovery comes from the realization that alternate contexts may reveal additional valuable information. The rate at which the data is storedis growing at a phenomenal rate. Asaresult,traditionaladhocmixturesofstatisticaltechniquesanddata managementtools are no longer adequate for analyzing this vast collection of data. Severaldomainswherelargevolumesofdataarestoredincentralizedor distributeddatabasesincludesapplicationslikeinelectroniccommerce,bio- formatics, computer security, Web intelligence, intelligent learning database systems,?nance,marketing,healthcare,telecommunications,andother?elds. E?cient tools and algorithms for knowledge discovery in large data sets have been devised during the recent years. These methods exploit the ca- bility of computers to search huge amounts of data in a fast and e?ective manner. However,the data to be analyzed is imprecise and a?icted with - certainty. In the case of heterogeneous data sources such as text and video, the data might moreover be ambiguous and partly con?icting. Besides, p- terns and relationships of interest are usually approximate. Thus, in order to make the information mining process more robust it requires tolerance toward imprecision, uncertainty and exceptions.

Soft Computing for Data Mining Applications

Author: K. R. Venugopal

Publisher: Springer

Published: 2009-02-24

Total Pages: 354

ISBN-13: 3642001939

DOWNLOAD EBOOK

Book Synopsis Soft Computing for Data Mining Applications by : K. R. Venugopal

Download or read book Soft Computing for Data Mining Applications written by K. R. Venugopal and published by Springer. This book was released on 2009-02-24 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: The authors have consolidated their research work in this volume titled Soft Computing for Data Mining Applications. The monograph gives an insight into the research in the ?elds of Data Mining in combination with Soft Computing methodologies. In these days, the data continues to grow - ponentially. Much of the data is implicitly or explicitly imprecise. Database discovery seeks to discover noteworthy, unrecognized associations between the data items in the existing database. The potential of discovery comes from the realization that alternate contexts may reveal additional valuable information. The rate at which the data is storedis growing at a phenomenal rate. Asaresult,traditionaladhocmixturesofstatisticaltechniquesanddata managementtools are no longer adequate for analyzing this vast collection of data. Severaldomainswherelargevolumesofdataarestoredincentralizedor distributeddatabasesincludesapplicationslikeinelectroniccommerce,bio- formatics, computer security, Web intelligence, intelligent learning database systems,?nance,marketing,healthcare,telecommunications,andother?elds. E?cient tools and algorithms for knowledge discovery in large data sets have been devised during the recent years. These methods exploit the ca- bility of computers to search huge amounts of data in a fast and e?ective manner. However,the data to be analyzed is imprecise and a?icted with - certainty. In the case of heterogeneous data sources such as text and video, the data might moreover be ambiguous and partly con?icting. Besides, p- terns and relationships of interest are usually approximate. Thus, in order to make the information mining process more robust it requires tolerance toward imprecision, uncertainty and exceptions.

Soft Computing for Knowledge Discovery and Data Mining

Author: Oded Maimon

Publisher: Springer Science & Business Media

Published: 2007-10-25

Total Pages: 431

ISBN-13: 038769935X

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Data Mining is the science and technology of exploring large and complex bodies of data in order to discover useful patterns. It is extremely important because it enables modeling and knowledge extraction from abundant data availability. This book introduces soft computing methods extending the envelope of problems that data mining can solve efficiently. It presents practical soft-computing approaches in data mining and includes various real-world case studies with detailed results.

Book Synopsis Soft Computing for Knowledge Discovery and Data Mining by : Oded Maimon

Download or read book Soft Computing for Knowledge Discovery and Data Mining written by Oded Maimon and published by Springer Science & Business Media. This book was released on 2007-10-25 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining is the science and technology of exploring large and complex bodies of data in order to discover useful patterns. It is extremely important because it enables modeling and knowledge extraction from abundant data availability. This book introduces soft computing methods extending the envelope of problems that data mining can solve efficiently. It presents practical soft-computing approaches in data mining and includes various real-world case studies with detailed results.

Data Mining

Author: Sushmita Mitra

Publisher: John Wiley & Sons

Published: 2005-01-21

Total Pages: 423

ISBN-13: 0471474886

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First title to ever present soft computing approaches and their application in data mining, along with the traditional hard-computing approaches Addresses the principles of multimedia data compression techniques (for image, video, text) and their role in data mining Discusses principles and classical algorithms on string matching and their role in data mining

Book Synopsis Data Mining by : Sushmita Mitra

Download or read book Data Mining written by Sushmita Mitra and published by John Wiley & Sons. This book was released on 2005-01-21 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt: First title to ever present soft computing approaches and their application in data mining, along with the traditional hard-computing approaches Addresses the principles of multimedia data compression techniques (for image, video, text) and their role in data mining Discusses principles and classical algorithms on string matching and their role in data mining

Intelligent Soft Computation and Evolving Data Mining: Integrating Advanced Technologies

Author: Wang, Leon Shyue-Liang

Publisher: IGI Global

Published: 2010-03-31

Total Pages: 516

ISBN-13: 1615207589

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"This book provides a reference to researchers, practitioners, and students in both soft computing and data mining communities for generating creative ideas of securing and managing data mining"--Provided by publisher.

Book Synopsis Intelligent Soft Computation and Evolving Data Mining: Integrating Advanced Technologies by : Wang, Leon Shyue-Liang

Download or read book Intelligent Soft Computation and Evolving Data Mining: Integrating Advanced Technologies written by Wang, Leon Shyue-Liang and published by IGI Global. This book was released on 2010-03-31 with total page 516 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book provides a reference to researchers, practitioners, and students in both soft computing and data mining communities for generating creative ideas of securing and managing data mining"--Provided by publisher.

Recent Advances on Soft Computing and Data Mining

Author: Tutut Herawan

Publisher: Springer

Published: 2016-12-27

Total Pages: 665

ISBN-13: 3319512811

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This book provides a comprehensive introduction and practical look at the concepts and techniques readers need to get the most out of their data in real-world, large-scale data mining projects. It also guides readers through the data-analytic thinking necessary for extracting useful knowledge and business value from the data. The book is based on the Soft Computing and Data Mining (SCDM-16) conference, which was held in Bandung, Indonesia on August 18th–20th 2016 to discuss the state of the art in soft computing techniques, and offer participants sufficient knowledge to tackle a wide range of complex systems. The scope of the conference is reflected in the book, which presents a balance of soft computing techniques and data mining approaches. The two constituents are introduced to the reader systematically and brought together using different combinations of applications and practices. It offers engineers, data analysts, practitioners, scientists and managers the insights into the concepts, tools and techniques employed, and as such enables them to better understand the design choice and options of soft computing techniques and data mining approaches that are necessary to thrive in this data-driven ecosystem.

Book Synopsis Recent Advances on Soft Computing and Data Mining by : Tutut Herawan

Download or read book Recent Advances on Soft Computing and Data Mining written by Tutut Herawan and published by Springer. This book was released on 2016-12-27 with total page 665 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive introduction and practical look at the concepts and techniques readers need to get the most out of their data in real-world, large-scale data mining projects. It also guides readers through the data-analytic thinking necessary for extracting useful knowledge and business value from the data. The book is based on the Soft Computing and Data Mining (SCDM-16) conference, which was held in Bandung, Indonesia on August 18th–20th 2016 to discuss the state of the art in soft computing techniques, and offer participants sufficient knowledge to tackle a wide range of complex systems. The scope of the conference is reflected in the book, which presents a balance of soft computing techniques and data mining approaches. The two constituents are introduced to the reader systematically and brought together using different combinations of applications and practices. It offers engineers, data analysts, practitioners, scientists and managers the insights into the concepts, tools and techniques employed, and as such enables them to better understand the design choice and options of soft computing techniques and data mining approaches that are necessary to thrive in this data-driven ecosystem.

Recent Advances on Soft Computing and Data Mining

Author: Rozaida Ghazali

Publisher: Springer

Published: 2018-01-11

Total Pages: 518

ISBN-13: 3319725505

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This book offers a systematic overview of the concepts and practical techniques that readers need to get the most out of their large-scale data mining projects and research studies. It guides them through the data-analytical thinking essential to extract useful information and obtain commercial value from the data. Presenting the outcomes of International Conference on Soft Computing and Data Mining (SCDM-2017), held in Johor, Malaysia on February 6–8, 2018, it provides a well-balanced integration of soft computing and data mining techniques. The two constituents are brought together in various combinations of applications and practices. To thrive in these data-driven ecosystems, researchers, engineers, data analysts, practitioners, and managers must understand the design choice and options of soft computing and data mining techniques, and as such this book is a valuable resource, helping readers solve complex benchmark problems and better appreciate the concepts, tools, and techniques employed.

Book Synopsis Recent Advances on Soft Computing and Data Mining by : Rozaida Ghazali

Download or read book Recent Advances on Soft Computing and Data Mining written by Rozaida Ghazali and published by Springer. This book was released on 2018-01-11 with total page 518 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a systematic overview of the concepts and practical techniques that readers need to get the most out of their large-scale data mining projects and research studies. It guides them through the data-analytical thinking essential to extract useful information and obtain commercial value from the data. Presenting the outcomes of International Conference on Soft Computing and Data Mining (SCDM-2017), held in Johor, Malaysia on February 6–8, 2018, it provides a well-balanced integration of soft computing and data mining techniques. The two constituents are brought together in various combinations of applications and practices. To thrive in these data-driven ecosystems, researchers, engineers, data analysts, practitioners, and managers must understand the design choice and options of soft computing and data mining techniques, and as such this book is a valuable resource, helping readers solve complex benchmark problems and better appreciate the concepts, tools, and techniques employed.

Recent Advances on Soft Computing and Data Mining

Author: Rozaida Ghazali

Publisher: Springer Nature

Published: 2019-12-04

Total Pages: 491

ISBN-13: 3030360563

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This book provides an introduction to data science and offers a practical overview of the concepts and techniques that readers need to get the most out of their large-scale data mining projects and research studies. It discusses data-analytical thinking, which is essential to extract useful knowledge and obtain commercial value from the data. Also known as data-driven science, soft computing and data mining disciplines cover a broad interdisciplinary range of scientific methods and processes. The book provides readers with sufficient knowledge to tackle a wide range of issues in complex systems, bringing together the scopes that integrate soft computing and data mining in various combinations of applications and practices, since to thrive in these data-driven ecosystems, researchers, data analysts and practitioners must understand the design choice and options of these approaches. This book helps readers to solve complex benchmark problems and to better appreciate the concepts, tools and techniques used.

Book Synopsis Recent Advances on Soft Computing and Data Mining by : Rozaida Ghazali

Download or read book Recent Advances on Soft Computing and Data Mining written by Rozaida Ghazali and published by Springer Nature. This book was released on 2019-12-04 with total page 491 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an introduction to data science and offers a practical overview of the concepts and techniques that readers need to get the most out of their large-scale data mining projects and research studies. It discusses data-analytical thinking, which is essential to extract useful knowledge and obtain commercial value from the data. Also known as data-driven science, soft computing and data mining disciplines cover a broad interdisciplinary range of scientific methods and processes. The book provides readers with sufficient knowledge to tackle a wide range of issues in complex systems, bringing together the scopes that integrate soft computing and data mining in various combinations of applications and practices, since to thrive in these data-driven ecosystems, researchers, data analysts and practitioners must understand the design choice and options of these approaches. This book helps readers to solve complex benchmark problems and to better appreciate the concepts, tools and techniques used.

Applied Soft Computing

Author: Samarjeet Borah

Publisher: CRC Press

Published: 2022-02-03

Total Pages: 286

ISBN-13: 1000406636

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This new volume explores a variety of modern techniques that deal with estimated models and give resolutions to complex real-life issues. Soft computing has played a crucial role not only with theoretical paradigms but is also popular for its pivotal role for designing a large variety of expert systems and artificial intelligence-based applications. Involving the concepts and practices of soft computing in conjunction with other frontier research domains, this book begins with the basics and goes on to explore a variety of modern applications of soft computing in areas such as approximate reasoning, artificial neural networks, Bayesian networks, big data analytics, bioinformatics, cloud computing, control systems, data mining, functional approximation, fuzzy logic, genetic and evolutionary algorithms, hybrid models, machine learning, metaheuristics, neuro fuzzy system, optimization, randomized searches, and swarm intelligence. This book will be helpful to a wide range of readers who wish to learn applications of soft computing approaches. It will be useful for academicians, researchers, students, and machine learning experts who use soft computing techniques and algorithms to develop cutting-edge artificial intelligence-based applications.

Book Synopsis Applied Soft Computing by : Samarjeet Borah

Download or read book Applied Soft Computing written by Samarjeet Borah and published by CRC Press. This book was released on 2022-02-03 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new volume explores a variety of modern techniques that deal with estimated models and give resolutions to complex real-life issues. Soft computing has played a crucial role not only with theoretical paradigms but is also popular for its pivotal role for designing a large variety of expert systems and artificial intelligence-based applications. Involving the concepts and practices of soft computing in conjunction with other frontier research domains, this book begins with the basics and goes on to explore a variety of modern applications of soft computing in areas such as approximate reasoning, artificial neural networks, Bayesian networks, big data analytics, bioinformatics, cloud computing, control systems, data mining, functional approximation, fuzzy logic, genetic and evolutionary algorithms, hybrid models, machine learning, metaheuristics, neuro fuzzy system, optimization, randomized searches, and swarm intelligence. This book will be helpful to a wide range of readers who wish to learn applications of soft computing approaches. It will be useful for academicians, researchers, students, and machine learning experts who use soft computing techniques and algorithms to develop cutting-edge artificial intelligence-based applications.

New Directions in Rough Sets, Data Mining, and Granular-Soft Computing

Author: Ning Zhong

Publisher: Springer

Published: 2004-06-22

Total Pages: 587

ISBN-13: 3540480617

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This book constitutes the refereed proceedings of the 7th International Workshop on Rough Sets, Fuzzy Sets, Data Mining, and Granular-Soft Computing, RSFDGrC'99, held in Yamaguchi, Japan, in November 1999. The 45 revised regular papers and 15 revised short papers presented together with four invited contributions were carefully reviewed and selected from 89 submissions. The book is divided into sections on rough computing: foundations and applications, rough set theory and applications, fuzzy set theory and applications, nonclassical logic and approximate reasoning, information granulation and granular computing, data mining and knowledge discovery, machine learning, and intelligent agents and systems.

Book Synopsis New Directions in Rough Sets, Data Mining, and Granular-Soft Computing by : Ning Zhong

Download or read book New Directions in Rough Sets, Data Mining, and Granular-Soft Computing written by Ning Zhong and published by Springer. This book was released on 2004-06-22 with total page 587 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 7th International Workshop on Rough Sets, Fuzzy Sets, Data Mining, and Granular-Soft Computing, RSFDGrC'99, held in Yamaguchi, Japan, in November 1999. The 45 revised regular papers and 15 revised short papers presented together with four invited contributions were carefully reviewed and selected from 89 submissions. The book is divided into sections on rough computing: foundations and applications, rough set theory and applications, fuzzy set theory and applications, nonclassical logic and approximate reasoning, information granulation and granular computing, data mining and knowledge discovery, machine learning, and intelligent agents and systems.