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Computational Intelligence In Data Mining Volume 3
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Book Synopsis Data Mining with Computational Intelligence by : Lipo Wang
Download or read book Data Mining with Computational Intelligence written by Lipo Wang and published by Springer Science & Business Media. This book was released on 2005-12-08 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Computational Intelligence in Data Mining by : G. Della Riccia
Download or read book Computational Intelligence in Data Mining written by G. Della Riccia and published by Springer Science & Business Media. This book was released on 2000-05-31 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Computational Intelligence in Data Mining - Volume 3 by : Lakhmi C. Jain
Download or read book Computational Intelligence in Data Mining - Volume 3 written by Lakhmi C. Jain and published by Springer. This book was released on 2014-12-11 with total page 717 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Computational Intelligence in Data Mining by : Himansu Sekhar Behera
Download or read book Computational Intelligence in Data Mining written by Himansu Sekhar Behera and published by Springer. This book was released on 2017-05-19 with total page 847 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Computational Intelligence in Data Mining—Volume 1 by : Himansu Sekhar Behera
Download or read book Computational Intelligence in Data Mining—Volume 1 written by Himansu Sekhar Behera and published by Springer. This book was released on 2015-12-08 with total page 494 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Foundations of Computational Intelligence by : Ajith Abraham
Download or read book Foundations of Computational Intelligence written by Ajith Abraham and published by Springer Science & Business Media. This book was released on 2009-04-27 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Computational Intelligence in Data Mining by : Giacomo Della Riccia
Download or read book Computational Intelligence in Data Mining written by Giacomo Della Riccia and published by . This book was released on 2014-09-01 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Computational Intelligent Data Analysis for Sustainable Development by : Ting Yu
Download or read book Computational Intelligent Data Analysis for Sustainable Development written by Ting Yu and published by CRC Press. This book was released on 2016-04-19 with total page 443 pages. Available in PDF, EPUB and Kindle. Book excerpt: Going beyond performing simple analyses, researchers involved in the highly dynamic field of computational intelligent data analysis design algorithms that solve increasingly complex data problems in changing environments, including economic, environmental, and social data. Computational Intelligent Data Analysis for Sustainable Development present
Book Synopsis Computational Intelligence in Data Mining - Volume 1 by : Lakhmi C. Jain
Download or read book Computational Intelligence in Data Mining - Volume 1 written by Lakhmi C. Jain and published by Springer. This book was released on 2014-12-10 with total page 713 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Data Mining written by Florin Gorunescu and published by Springer Science & Business Media. This book was released on 2011-03-10 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: The knowledge discovery process is as old as Homo sapiens. Until some time ago this process was solely based on the ‘natural personal' computer provided by Mother Nature. Fortunately, in recent decades the problem has begun to be solved based on the development of the Data mining technology, aided by the huge computational power of the 'artificial' computers. Digging intelligently in different large databases, data mining aims to extract implicit, previously unknown and potentially useful information from data, since “knowledge is power”. The goal of this book is to provide, in a friendly way, both theoretical concepts and, especially, practical techniques of this exciting field, ready to be applied in real-world situations. Accordingly, it is meant for all those who wish to learn how to explore and analysis of large quantities of data in order to discover the hidden nugget of information.
Book Synopsis Introduction to Data Mining and its Applications by : S. Sumathi
Download or read book Introduction to Data Mining and its Applications written by S. Sumathi and published by Springer. This book was released on 2006-10-12 with total page 828 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Data Mining With Computational Intelligence by : Wang
Download or read book Data Mining With Computational Intelligence written by Wang and published by . This book was released on 2009-10-01 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Machine Learning and Data Mining by : Igor Kononenko
Download or read book Machine Learning and Data Mining written by Igor Kononenko and published by Elsevier. This book was released on 2007-04-30 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Computational Intelligence in Data Mining by : Himansu Sekhar Behera
Download or read book Computational Intelligence in Data Mining written by Himansu Sekhar Behera and published by Springer. This book was released on 2018-07-03 with total page 896 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Computational Intelligence in Data Mining by : Himansu Sekhar Behera
Download or read book Computational Intelligence in Data Mining written by Himansu Sekhar Behera and published by Springer. This book was released on 2019-08-17 with total page 801 pages. Available in PDF, EPUB and Kindle. Book excerpt: This proceeding discuss the latest solutions, scientific findings and methods for solving intriguing problems in the fields of data mining, computational intelligence, big data analytics, and soft computing. This gathers outstanding papers from the fifth International Conference on “Computational Intelligence in Data Mining” (ICCIDM), and offer a “sneak preview” of the strengths and weaknesses of trending applications, together with exciting advances in computational intelligence, data mining, and related fields.
Book Synopsis Pocket Data Mining by : Mohamed Medhat Gaber
Download or read book Pocket Data Mining written by Mohamed Medhat Gaber and published by Springer Science & Business Media. This book was released on 2013-10-19 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: Owing to continuous advances in the computational power of handheld devices like smartphones and tablet computers, it has become possible to perform Big Data operations including modern data mining processes onboard these small devices. A decade of research has proved the feasibility of what has been termed as Mobile Data Mining, with a focus on one mobile device running data mining processes. However, it is not before 2010 until the authors of this book initiated the Pocket Data Mining (PDM) project exploiting the seamless communication among handheld devices performing data analysis tasks that were infeasible until recently. PDM is the process of collaboratively extracting knowledge from distributed data streams in a mobile computing environment. This book provides the reader with an in-depth treatment on this emerging area of research. Details of techniques used and thorough experimental studies are given. More importantly and exclusive to this book, the authors provide detailed practical guide on the deployment of PDM in the mobile environment. An important extension to the basic implementation of PDM dealing with concept drift is also reported. In the era of Big Data, potential applications of paramount importance offered by PDM in a variety of domains including security, business and telemedicine are discussed.
Book Synopsis Data Mining: Foundations and Intelligent Paradigms by : Dawn E. Holmes
Download or read book Data Mining: Foundations and Intelligent Paradigms written by Dawn E. Holmes and published by Springer Science & Business Media. This book was released on 2012-01-12 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
