Computational Intelligence In Data Mining Volume 3

Author : Lipo Wang,Xiuju Fu
Publisher : Springer Science & Business Media
Page : 280 pages
File Size : 53,5 Mb
Release : 2005-12-08
Category : Computers
ISBN : 9783540288039

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Data Mining with Computational Intelligence by Lipo Wang,Xiuju Fu Pdf

Finding information hidden in data is as theoretically difficult as it is practically important. With the objective of discovering unknown patterns from data, the methodologies of data mining were derived from statistics, machine learning, and artificial intelligence, and are being used successfully in application areas such as bioinformatics, banking, retail, and many others. Wang and Fu present in detail the state of the art on how to utilize fuzzy neural networks, multilayer perceptron neural networks, radial basis function neural networks, genetic algorithms, and support vector machines in such applications. They focus on three main data mining tasks: data dimensionality reduction, classification, and rule extraction. The book is targeted at researchers in both academia and industry, while graduate students and developers of data mining systems will also profit from the detailed algorithmic descriptions.

Author : Lakhmi C. Jain,Himansu Sekhar Behera,Jyotsna Kumar Mandal,Durga Prasad Mohapatra
Publisher : Springer
Page : 717 pages
File Size : 41,5 Mb
Release : 2014-12-11
Category : Technology & Engineering
ISBN : 9788132222026

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Computational Intelligence in Data Mining - Volume 3 by Lakhmi C. Jain,Himansu Sekhar Behera,Jyotsna Kumar Mandal,Durga Prasad Mohapatra Pdf

The contributed volume aims to explicate and address the difficulties and challenges for the seamless integration of two core disciplines of computer science, i.e., computational intelligence and data mining. Data Mining aims at the automatic discovery of underlying non-trivial knowledge from datasets by applying intelligent analysis techniques. The interest in this research area has experienced a considerable growth in the last years due to two key factors: (a) knowledge hidden in organizations’ databases can be exploited to improve strategic and managerial decision-making; (b) the large volume of data managed by organizations makes it impossible to carry out a manual analysis. The book addresses different methods and techniques of integration for enhancing the overall goal of data mining. The book helps to disseminate the knowledge about some innovative, active research directions in the field of data mining, machine and computational intelligence, along with some current issues and applications of related topics.

Author : Giacomo Della Riccia,Rudolf Kruse,Hans-J. Lenz
Publisher : Springer
Page : 169 pages
File Size : 52,7 Mb
Release : 2014-05-04
Category : Computers
ISBN : 9783709125885

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Computational Intelligence in Data Mining by Giacomo Della Riccia,Rudolf Kruse,Hans-J. Lenz Pdf

The book aims to merge Computational Intelligence with Data Mining, which are both hot topics of current research and industrial development, Computational Intelligence, incorporates techniques like data fusion, uncertain reasoning, heuristic search, learning, and soft computing. Data Mining focuses on unscrambling unknown patterns or structures in very large data sets. Under the headline "Discovering Structures in Large Databases” the book starts with a unified view on ‘Data Mining and Statistics – A System Point of View’. Two special techniques follow: ‘Subgroup Mining’, and ‘Data Mining with Possibilistic Graphical Models’. "Data Fusion and Possibilistic or Fuzzy Data Analysis” is the next area of interest. An overview of possibilistic logic, nonmonotonic reasoning and data fusion is given, the coherence problem between data and non-linear fuzzy models is tackled, and outlier detection based on learning of fuzzy models is studied. In the domain of "Classification and Decomposition” adaptive clustering and visualisation of high dimensional data sets is introduced. Finally, in the section "Learning and Data Fusion” learning of special multi-agents of virtual soccer is considered. The last topic is on data fusion based on stochastic models.

Author : Himansu Sekhar Behera,Durga Prasad Mohapatra
Publisher : Springer
Page : 847 pages
File Size : 43,5 Mb
Release : 2017-05-19
Category : Technology & Engineering
ISBN : 9789811038747

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Computational Intelligence in Data Mining by Himansu Sekhar Behera,Durga Prasad Mohapatra Pdf

The book presents high quality papers presented at the International Conference on Computational Intelligence in Data Mining (ICCIDM 2016) organized by School of Computer Engineering, Kalinga Institute of Industrial Technology (KIIT), Bhubaneswar, Odisha, India during December 10 – 11, 2016. The book disseminates the knowledge about innovative, active research directions in the field of data mining, machine and computational intelligence, along with current issues and applications of related topics. The volume aims to explicate and address the difficulties and challenges that of seamless integration of the two core disciplines of computer science.

Author : Ajith Abraham,Aboul-Ella Hassanien,André Ponce de Leon F. de Carvalho,Vaclav Snášel
Publisher : Springer
Page : 400 pages
File Size : 48,9 Mb
Release : 2009-05-01
Category : Technology & Engineering
ISBN : 9783642010910

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Foundations of Computational Intelligence by Ajith Abraham,Aboul-Ella Hassanien,André Ponce de Leon F. de Carvalho,Vaclav Snášel Pdf

Foundations of Computational Intelligence Volume 6: Data Mining: Theoretical Foundations and Applications Finding information hidden in data is as theoretically difficult as it is practically important. With the objective of discovering unknown patterns from data, the methodologies of data mining were derived from statistics, machine learning, and artificial intelligence, and are being used successfully in application areas such as bioinformatics, business, health care, banking, retail, and many others. Advanced representation schemes and computational intelligence techniques such as rough sets, neural networks; decision trees; fuzzy logic; evolutionary algorithms; arti- cial immune systems; swarm intelligence; reinforcement learning, association rule mining, Web intelligence paradigms etc. have proved valuable when they are - plied to Data Mining problems. Computational tools or solutions based on intel- gent systems are being used with great success in Data Mining applications. It is also observed that strong scientific advances have been made when issues from different research areas are integrated. This Volume comprises of 15 chapters including an overview chapter providing an up-to-date and state-of-the research on the applications of Computational Int- ligence techniques for Data Mining. The book is divided into 3 parts: Part-I: Data Click Streams and Temporal Data Mining Part-II: Text and Rule Mining Part-III: Applications Part I on Data Click Streams and Temporal Data Mining contains four chapters that describe several approaches in Data Click Streams and Temporal Data Mining.

Author : Giacomo Della Riccia,Rudolf Kruse,Hans J. Lenz
Publisher : Unknown
Page : 176 pages
File Size : 40,7 Mb
Release : 2014-09-01
Category : Electronic
ISBN : 3709125898

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Computational Intelligence in Data Mining by Giacomo Della Riccia,Rudolf Kruse,Hans J. Lenz Pdf

Author : Himansu Sekhar Behera,Durga Prasad Mohapatra
Publisher : Springer
Page : 494 pages
File Size : 40,6 Mb
Release : 2015-12-08
Category : Technology & Engineering
ISBN : 9788132227342

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Computational Intelligence in Data Mining—Volume 1 by Himansu Sekhar Behera,Durga Prasad Mohapatra Pdf

The book is a collection of high-quality peer-reviewed research papers presented in the Second International Conference on Computational Intelligence in Data Mining (ICCIDM 2015) held at Bhubaneswar, Odisha, India during 5 – 6 December 2015. The two-volume Proceedings address the difficulties and challenges for the seamless integration of two core disciplines of computer science, i.e., computational intelligence and data mining. The book addresses different methods and techniques of integration for enhancing the overall goal of data mining. The book helps to disseminate the knowledge about some innovative, active research directions in the field of data mining, machine and computational intelligence, along with some current issues and applications of related topics.

Author : Dawn E. Holmes,Lakhmi C Jain
Publisher : Springer Science & Business Media
Page : 364 pages
File Size : 48,6 Mb
Release : 2012-01-12
Category : Technology & Engineering
ISBN : 9783642231513

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Data Mining: Foundations and Intelligent Paradigms by Dawn E. Holmes,Lakhmi C Jain Pdf

There are many invaluable books available on data mining theory and applications. However, in compiling a volume titled “DATA MINING: Foundations and Intelligent Paradigms: Volume 3: Medical, Health, Social, Biological and other Applications” we wish to introduce some of the latest developments to a broad audience of both specialists and non-specialists in this field.

Author : Lakhmi C. Jain,Himansu Sekhar Behera,Jyotsna Kumar Mandal,Durga Prasad Mohapatra
Publisher : Springer
Page : 713 pages
File Size : 51,7 Mb
Release : 2014-12-10
Category : Technology & Engineering
ISBN : 9788132222057

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Computational Intelligence in Data Mining - Volume 1 by Lakhmi C. Jain,Himansu Sekhar Behera,Jyotsna Kumar Mandal,Durga Prasad Mohapatra Pdf

The contributed volume aims to explicate and address the difficulties and challenges for the seamless integration of two core disciplines of computer science, i.e., computational intelligence and data mining. Data Mining aims at the automatic discovery of underlying non-trivial knowledge from datasets by applying intelligent analysis techniques. The interest in this research area has experienced a considerable growth in the last years due to two key factors: (a) knowledge hidden in organizations’ databases can be exploited to improve strategic and managerial decision-making; (b) the large volume of data managed by organizations makes it impossible to carry out a manual analysis. The book addresses different methods and techniques of integration for enhancing the overall goal of data mining. The book helps to disseminate the knowledge about some innovative, active research directions in the field of data mining, machine and computational intelligence, along with some current issues and applications of related topics.

Author : Himansu Sekhar Behera,Durga Prasad Mohapatra
Publisher : Springer
Page : 520 pages
File Size : 48,9 Mb
Release : 2015-12-09
Category : Technology & Engineering
ISBN : 9788132227311

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Computational Intelligence in Data Mining—Volume 2 by Himansu Sekhar Behera,Durga Prasad Mohapatra Pdf

The book is a collection of high-quality peer-reviewed research papers presented in the Second International Conference on Computational Intelligence in Data Mining (ICCIDM 2015) held at Bhubaneswar, Odisha, India during 5 – 6 December 2015. The two-volume Proceedings address the difficulties and challenges for the seamless integration of two core disciplines of computer science, i.e., computational intelligence and data mining. The book addresses different methods and techniques of integration for enhancing the overall goal of data mining. The book helps to disseminate the knowledge about some innovative, active research directions in the field of data mining, machine and computational intelligence, along with some current issues and applications of related topics.

Author : Wang
Publisher : Unknown
Page : 288 pages
File Size : 45,6 Mb
Release : 2009-10-01
Category : Electronic
ISBN : 8184893582

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Data Mining With Computational Intelligence by Wang Pdf

Author : Himansu Sekhar Behera,Janmenjoy Nayak,Bighnaraj Naik,Ajith Abraham
Publisher : Springer
Page : 896 pages
File Size : 41,9 Mb
Release : 2018-07-03
Category : Technology & Engineering
ISBN : 9789811080555

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Computational Intelligence in Data Mining by Himansu Sekhar Behera,Janmenjoy Nayak,Bighnaraj Naik,Ajith Abraham Pdf

The International Conference on “Computational Intelligence in Data Mining” (ICCIDM), after three successful versions, has reached to its fourth version with a lot of aspiration. The best selected conference papers are reviewed and compiled to form this volume. The proceedings discusses the latest solutions, scientific results and methods in solving intriguing problems in the fields of data mining, computational intelligence, big data analytics, and soft computing. The volume presents a sneak preview into the strengths and weakness of trending applications and research findings in the field of computational intelligence and data mining along with related field.

Author : Ajith Abraham,Aboul-Ella Hassanien,André Ponce de Leon F. de Carvalho,Vaclav Sná#el
Publisher : Springer Science & Business Media
Page : 397 pages
File Size : 48,8 Mb
Release : 2009-04-27
Category : Mathematics
ISBN : 9783642010903

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Foundations of Computational Intelligence by Ajith Abraham,Aboul-Ella Hassanien,André Ponce de Leon F. de Carvalho,Vaclav Sná#el Pdf

Foundations of Computational Intelligence Volume 6: Data Mining: Theoretical Foundations and Applications Finding information hidden in data is as theoretically difficult as it is practically important. With the objective of discovering unknown patterns from data, the methodologies of data mining were derived from statistics, machine learning, and artificial intelligence, and are being used successfully in application areas such as bioinformatics, business, health care, banking, retail, and many others. Advanced representation schemes and computational intelligence techniques such as rough sets, neural networks; decision trees; fuzzy logic; evolutionary algorithms; arti- cial immune systems; swarm intelligence; reinforcement learning, association rule mining, Web intelligence paradigms etc. have proved valuable when they are - plied to Data Mining problems. Computational tools or solutions based on intel- gent systems are being used with great success in Data Mining applications. It is also observed that strong scientific advances have been made when issues from different research areas are integrated. This Volume comprises of 15 chapters including an overview chapter providing an up-to-date and state-of-the research on the applications of Computational Int- ligence techniques for Data Mining. The book is divided into 3 parts: Part-I: Data Click Streams and Temporal Data Mining Part-II: Text and Rule Mining Part-III: Applications Part I on Data Click Streams and Temporal Data Mining contains four chapters that describe several approaches in Data Click Streams and Temporal Data Mining.

Author : Igor Kononenko,Matjaz Kukar
Publisher : Elsevier
Page : 480 pages
File Size : 48,8 Mb
Release : 2007-04-30
Category : Computers
ISBN : 9780857099440

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Machine Learning and Data Mining by Igor Kononenko,Matjaz Kukar Pdf

Data mining is often referred to by real-time users and software solutions providers as knowledge discovery in databases (KDD). Good data mining practice for business intelligence (the art of turning raw software into meaningful information) is demonstrated by the many new techniques and developments in the conversion of fresh scientific discovery into widely accessible software solutions. This book has been written as an introduction to the main issues associated with the basics of machine learning and the algorithms used in data mining. Suitable for advanced undergraduates and their tutors at postgraduate level in a wide area of computer science and technology topics as well as researchers looking to adapt various algorithms for particular data mining tasks. A valuable addition to the libraries and bookshelves of the many companies who are using the principles of data mining (or KDD) to effectively deliver solid business and industry solutions. Provides an introduction to the main issues associated with the basics of machine learning and the algorithms used in data mining A valuable addition to the libraries and bookshelves of companies using the principles of data mining (or KDD) to effectively deliver solid business and industry solutions

Author : S. Sumathi,S.N. Sivanandam
Publisher : Springer
Page : 828 pages
File Size : 50,8 Mb
Release : 2006-10-12
Category : Computers
ISBN : 9783540343516

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Introduction to Data Mining and its Applications by S. Sumathi,S.N. Sivanandam Pdf

This book explores the concepts of data mining and data warehousing, a promising and flourishing frontier in database systems, and presents a broad, yet in-depth overview of the field of data mining. Data mining is a multidisciplinary field, drawing work from areas including database technology, artificial intelligence, machine learning, neural networks, statistics, pattern recognition, knowledge based systems, knowledge acquisition, information retrieval, high performance computing and data visualization.