Soft Computing For Data Mining Applications

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Soft Computing for Data Mining Applications

Author : K. R. Venugopal
Publisher : Springer
ISBN 13 : 3642001939
Total Pages : 341 pages
Book Rating : 4.6/5 (42 download)

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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 341 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
ISBN 13 : 038769935X
Total Pages : 431 pages
Book Rating : 4.3/5 (876 download)

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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
ISBN 13 : 0471474886
Total Pages : 423 pages
Book Rating : 4.4/5 (714 download)

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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
ISBN 13 : 1615207589
Total Pages : 516 pages
Book Rating : 4.6/5 (152 download)

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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
ISBN 13 : 3319512811
Total Pages : 665 pages
Book Rating : 4.3/5 (195 download)

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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
ISBN 13 : 3319725505
Total Pages : 518 pages
Book Rating : 4.3/5 (197 download)

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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.

Soft Computing Applications for Database Technologies

Author : K. Anbumani
Publisher : IGI Global
ISBN 13 : 1605668141
Total Pages : 348 pages
Book Rating : 4.6/5 (56 download)

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Book Synopsis Soft Computing Applications for Database Technologies by : K. Anbumani

Download or read book Soft Computing Applications for Database Technologies written by K. Anbumani and published by IGI Global. This book was released on 2010-01-01 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book investigates the advent of soft computing and its applications in database technologies"--Provided by publisher.

Recent Advances on Soft Computing and Data Mining

Author : Rozaida Ghazali
Publisher : Springer Nature
ISBN 13 : 3030360563
Total Pages : 491 pages
Book Rating : 4.0/5 (33 download)

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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.

Soft Computing in Data Science

Author : Azlinah Mohamed
Publisher : Springer Nature
ISBN 13 : 9811673349
Total Pages : 450 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Soft Computing in Data Science by : Azlinah Mohamed

Download or read book Soft Computing in Data Science written by Azlinah Mohamed and published by Springer Nature. This book was released on 2021-10-28 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 6th International Conference on Soft Computing in Data Science, SCDS 2021, which was held virtually in November 2021. The 31 revised full papers presented were carefully reviewed and selected from 79 submissions. The papers are organized in topical sections on AI techniques and applications; data analytics and technologies; data mining and image processing; machine & statistical learning.

Applied Soft Computing

Author : Samarjeet Borah
Publisher : CRC Press
ISBN 13 : 1000406636
Total Pages : 286 pages
Book Rating : 4.0/5 (4 download)

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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
ISBN 13 : 3540480617
Total Pages : 566 pages
Book Rating : 4.5/5 (44 download)

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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 566 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.

Soft Computing for Data Analytics, Classification Model, and Control

Author : Deepak Gupta
Publisher : Springer Nature
ISBN 13 : 3030920267
Total Pages : 165 pages
Book Rating : 4.0/5 (39 download)

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Book Synopsis Soft Computing for Data Analytics, Classification Model, and Control by : Deepak Gupta

Download or read book Soft Computing for Data Analytics, Classification Model, and Control written by Deepak Gupta and published by Springer Nature. This book was released on 2022-01-30 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a set of soft computing approaches and their application in data analytics, classification model, and control. The basics of fuzzy logic implementation for advanced hybrid fuzzy driven optimization methods has been covered in the book. The various soft computing techniques, including Fuzzy Logic, Rough Sets, Neutrosophic Sets, Type-2 Fuzzy logic, Neural Networks, Generative Adversarial Networks, and Evolutionary Computation have been discussed and they are used on variety of applications including data analytics, classification model, and control. The book is divided into two thematic parts. The first thematic section covers the various soft computing approaches for text classification and data analysis, while the second section focuses on the fuzzy driven optimization methods for the control systems. The chapters has been written and edited by active researchers, which cover hypotheses and practical considerations; provide insights into the design of hybrid algorithms for applications in data analytics, classification model, and engineering control.

Applications of Big Data in Large- and Small-Scale Systems

Author : Goundar, Sam
Publisher : IGI Global
ISBN 13 : 1799866750
Total Pages : 377 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Applications of Big Data in Large- and Small-Scale Systems by : Goundar, Sam

Download or read book Applications of Big Data in Large- and Small-Scale Systems written by Goundar, Sam and published by IGI Global. This book was released on 2021-01-15 with total page 377 pages. Available in PDF, EPUB and Kindle. Book excerpt: With new technologies, such as computer vision, internet of things, mobile computing, e-governance and e-commerce, and wide applications of social media, organizations generate a huge volume of data and at a much faster rate than several years ago. Big data in large-/small-scale systems, characterized by high volume, diversity, and velocity, increasingly drives decision making and is changing the landscape of business intelligence. From governments to private organizations, from communities to individuals, all areas are being affected by this shift. There is a high demand for big data analytics that offer insights for computing efficiency, knowledge discovery, problem solving, and event prediction. To handle this demand and this increase in big data, there needs to be research on innovative and optimized machine learning algorithms in both large- and small-scale systems. Applications of Big Data in Large- and Small-Scale Systems includes state-of-the-art research findings on the latest development, up-to-date issues, and challenges in the field of big data and presents the latest innovative and intelligent applications related to big data. This book encompasses big data in various multidisciplinary fields from the medical field to agriculture, business research, and smart cities. While highlighting topics including machine learning, cloud computing, data visualization, and more, this book is a valuable reference tool for computer scientists, data scientists and analysts, engineers, practitioners, stakeholders, researchers, academicians, and students interested in the versatile and innovative use of big data in both large-scale and small-scale systems.

Data Mining and Computational Intelligence

Author : Abraham Kandel
Publisher : Physica
ISBN 13 : 3790818259
Total Pages : 364 pages
Book Rating : 4.7/5 (98 download)

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Book Synopsis Data Mining and Computational Intelligence by : Abraham Kandel

Download or read book Data Mining and Computational Intelligence written by Abraham Kandel and published by Physica. This book was released on 2013-11-11 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many business decisions are made in the absence of complete information about the decision consequences. Credit lines are approved without knowing the future behavior of the customers; stocks are bought and sold without knowing their future prices; parts are manufactured without knowing all the factors affecting their final quality; etc. All these cases can be categorized as decision making under uncertainty. Decision makers (human or automated) can handle uncertainty in different ways. Deferring the decision due to the lack of sufficient information may not be an option, especially in real-time systems. Sometimes expert rules, based on experience and intuition, are used. Decision tree is a popular form of representing a set of mutually exclusive rules. An example of a two-branch tree is: if a credit applicant is a student, approve; otherwise, decline. Expert rules are usually based on some hidden assumptions, which are trying to predict the decision consequences. A hidden assumption of the last rule set is: a student will be a profitable customer. Since the direct predictions of the future may not be accurate, a decision maker can consider using some information from the past. The idea is to utilize the potential similarity between the patterns of the past (e.g., "most students used to be profitable") and the patterns of the future (e.g., "students will be profitable").

Data Mining, Rough Sets and Granular Computing

Author : Tsau Young Lin
Publisher : Springer Science & Business Media
ISBN 13 : 9783790814613
Total Pages : 556 pages
Book Rating : 4.8/5 (146 download)

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Book Synopsis Data Mining, Rough Sets and Granular Computing by : Tsau Young Lin

Download or read book Data Mining, Rough Sets and Granular Computing written by Tsau Young Lin and published by Springer Science & Business Media. This book was released on 2002-04-10 with total page 556 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the past few years, data mining has grown rapidly in visibility and importance within information processing and decision analysis. This is par ticularly true in the realm of e-commerce, where data mining is moving from a "nice-to-have" to a "must-have" status. In a different though related context, a new computing methodology called granular computing is emerging as a powerful tool for the conception, analysis and design of information/intelligent systems. In essence, data mining deals with summarization of information which is resident in large data sets, while granular computing plays a key role in the summarization process by draw ing together points (objects) which are related through similarity, proximity or functionality. In this perspective, granular computing has a position of centrality in data mining. Another methodology which has high relevance to data mining and plays a central role in this volume is that of rough set theory. Basically, rough set theory may be viewed as a branch of granular computing. However, its applications to data mining have predated that of granular computing.

Soft Computing in Data Science

Author : Azlinah Mohamed
Publisher : Springer
ISBN 13 : 9811072426
Total Pages : 317 pages
Book Rating : 4.8/5 (11 download)

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Book Synopsis Soft Computing in Data Science by : Azlinah Mohamed

Download or read book Soft Computing in Data Science written by Azlinah Mohamed and published by Springer. This book was released on 2017-11-23 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the International Conference on Soft Computing in Data Science, SCDS 2017, held in Yogyakarta, Indonesia, November 27-28, 2017. The 26 revised full papers presented were carefully reviewed and selected from 68 submissions. The papers are organized in topical sections on deep learning and real-time classification; image feature classification and extraction; classification, clustering, visualization; applications of machine learning; data visualization; fuzzy logic; prediction models and e-learning; text and sentiment analytics.

Information Fusion in Data Mining

Author : Prof. Vicenç Torra
Publisher : Springer
ISBN 13 : 3540365192
Total Pages : 232 pages
Book Rating : 4.5/5 (43 download)

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Book Synopsis Information Fusion in Data Mining by : Prof. Vicenç Torra

Download or read book Information Fusion in Data Mining written by Prof. Vicenç Torra and published by Springer. This book was released on 2013-06-05 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information fusion is becoming a major requirement in data mining and knowledge discovery in databases. This book presents some recent fusion techniques that are currently in use in data mining, as well as data mining applications that use information fusion. Special focus of the book is on information fusion in preprocessing, model building and information extraction with various applications.