Data Mining and Knowledge Discovery in Real Life Applications

Data Mining and Knowledge Discovery in Real Life Applications

Author: Julio Ponce

Publisher: BoD – Books on Demand

Published: 2009-01-01

Total Pages: 404

ISBN-13: 390261353X

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This book presents four different ways of theoretical and practical advances and applications of data mining in different promising areas like Industrialist, Biological, and Social. Twenty six chapters cover different special topics with proposed novel ideas. Each chapter gives an overview of the subjects and some of the chapters have cases with offered data mining solutions. We hope that this book will be a useful aid in showing a right way for the students, researchers and practitioners in their studies.


Book Synopsis Data Mining and Knowledge Discovery in Real Life Applications by : Julio Ponce

Download or read book Data Mining and Knowledge Discovery in Real Life Applications written by Julio Ponce and published by BoD – Books on Demand. This book was released on 2009-01-01 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents four different ways of theoretical and practical advances and applications of data mining in different promising areas like Industrialist, Biological, and Social. Twenty six chapters cover different special topics with proposed novel ideas. Each chapter gives an overview of the subjects and some of the chapters have cases with offered data mining solutions. We hope that this book will be a useful aid in showing a right way for the students, researchers and practitioners in their studies.


Data Mining and Knowledge Discovery via Logic-Based Methods

Data Mining and Knowledge Discovery via Logic-Based Methods

Author: Evangelos Triantaphyllou

Publisher: Springer Science & Business Media

Published: 2010-06-08

Total Pages: 371

ISBN-13: 144191630X

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The importance of having ef cient and effective methods for data mining and kn- ledge discovery (DM&KD), to which the present book is devoted, grows every day and numerous such methods have been developed in recent decades. There exists a great variety of different settings for the main problem studied by data mining and knowledge discovery, and it seems that a very popular one is formulated in terms of binary attributes. In this setting, states of nature of the application area under consideration are described by Boolean vectors de ned on some attributes. That is, by data points de ned in the Boolean space of the attributes. It is postulated that there exists a partition of this space into two classes, which should be inferred as patterns on the attributes when only several data points are known, the so-called positive and negative training examples. The main problem in DM&KD is de ned as nding rules for recognizing (cl- sifying) new data points of unknown class, i. e. , deciding which of them are positive and which are negative. In other words, to infer the binary value of one more attribute, called the goal or class attribute. To solve this problem, some methods have been suggested which construct a Boolean function separating the two given sets of positive and negative training data points.


Book Synopsis Data Mining and Knowledge Discovery via Logic-Based Methods by : Evangelos Triantaphyllou

Download or read book Data Mining and Knowledge Discovery via Logic-Based Methods written by Evangelos Triantaphyllou and published by Springer Science & Business Media. This book was released on 2010-06-08 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: The importance of having ef cient and effective methods for data mining and kn- ledge discovery (DM&KD), to which the present book is devoted, grows every day and numerous such methods have been developed in recent decades. There exists a great variety of different settings for the main problem studied by data mining and knowledge discovery, and it seems that a very popular one is formulated in terms of binary attributes. In this setting, states of nature of the application area under consideration are described by Boolean vectors de ned on some attributes. That is, by data points de ned in the Boolean space of the attributes. It is postulated that there exists a partition of this space into two classes, which should be inferred as patterns on the attributes when only several data points are known, the so-called positive and negative training examples. The main problem in DM&KD is de ned as nding rules for recognizing (cl- sifying) new data points of unknown class, i. e. , deciding which of them are positive and which are negative. In other words, to infer the binary value of one more attribute, called the goal or class attribute. To solve this problem, some methods have been suggested which construct a Boolean function separating the two given sets of positive and negative training data points.


Handbook of Data Mining and Knowledge Discovery

Handbook of Data Mining and Knowledge Discovery

Author: Jan M. Żytkow

Publisher: Oxford University Press, USA

Published: 2002

Total Pages: 1026

ISBN-13: 9780195118315

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Data mining, or knowledge discovery in databases (KDD), is one of the fastest growing areas in computing application: it offers powerful tools to analyze the many large data bases used in business, science, and industry. Data mining technology searches large databases to extract information and patterns that can be translated into useful applications, such as classifying or predicting customer behavior. This book brings together fundamental knowledge on all aspects of data mining--concepts, theory, techniques, applications, and case studies. Designed for students and professionals in such fields as computing applications, information systems management and strategic research and management, the Handbook is a comprehensive guide to essential tools and technology, from neural networks to artificial intelligence. There is a strong emphasis on real-world case studies in such areas as banking, finance, marketing management, real estate, engineering, medicine, pharmacology, and the biosciences. A much needed resource on one of the fastest growing areas of computer applications--the development and use of tools to analyze, interpret, and make use of the enormous amounts of information stored in the world's databases.


Book Synopsis Handbook of Data Mining and Knowledge Discovery by : Jan M. Żytkow

Download or read book Handbook of Data Mining and Knowledge Discovery written by Jan M. Żytkow and published by Oxford University Press, USA. This book was released on 2002 with total page 1026 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining, or knowledge discovery in databases (KDD), is one of the fastest growing areas in computing application: it offers powerful tools to analyze the many large data bases used in business, science, and industry. Data mining technology searches large databases to extract information and patterns that can be translated into useful applications, such as classifying or predicting customer behavior. This book brings together fundamental knowledge on all aspects of data mining--concepts, theory, techniques, applications, and case studies. Designed for students and professionals in such fields as computing applications, information systems management and strategic research and management, the Handbook is a comprehensive guide to essential tools and technology, from neural networks to artificial intelligence. There is a strong emphasis on real-world case studies in such areas as banking, finance, marketing management, real estate, engineering, medicine, pharmacology, and the biosciences. A much needed resource on one of the fastest growing areas of computer applications--the development and use of tools to analyze, interpret, and make use of the enormous amounts of information stored in the world's databases.


Data Mining and Knowledge Discovery Approaches Based on Rule Induction Techniques

Data Mining and Knowledge Discovery Approaches Based on Rule Induction Techniques

Author: Evangelos Triantaphyllou

Publisher: Springer Science & Business Media

Published: 2006-09-10

Total Pages: 784

ISBN-13: 0387342966

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This book outlines the core theory and practice of data mining and knowledge discovery (DM & KD) examining theoretical foundations for various methods, and presenting an array of examples, many drawn from real-life applications. Most theoretical developments are accompanied by extensive empirical analysis, offering a deep insight into both theoretical and practical aspects of the subject. The book presents the combined research experiences of 40 expert contributors of world renown.


Book Synopsis Data Mining and Knowledge Discovery Approaches Based on Rule Induction Techniques by : Evangelos Triantaphyllou

Download or read book Data Mining and Knowledge Discovery Approaches Based on Rule Induction Techniques written by Evangelos Triantaphyllou and published by Springer Science & Business Media. This book was released on 2006-09-10 with total page 784 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book outlines the core theory and practice of data mining and knowledge discovery (DM & KD) examining theoretical foundations for various methods, and presenting an array of examples, many drawn from real-life applications. Most theoretical developments are accompanied by extensive empirical analysis, offering a deep insight into both theoretical and practical aspects of the subject. The book presents the combined research experiences of 40 expert contributors of world renown.


Knowledge Discovery from Data Streams

Knowledge Discovery from Data Streams

Author: Joao Gama

Publisher: CRC Press

Published: 2010-05-25

Total Pages: 256

ISBN-13: 1439826129

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Since the beginning of the Internet age and the increased use of ubiquitous computing devices, the large volume and continuous flow of distributed data have imposed new constraints on the design of learning algorithms. Exploring how to extract knowledge structures from evolving and time-changing data, Knowledge Discovery from Data Streams presents


Book Synopsis Knowledge Discovery from Data Streams by : Joao Gama

Download or read book Knowledge Discovery from Data Streams written by Joao Gama and published by CRC Press. This book was released on 2010-05-25 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the beginning of the Internet age and the increased use of ubiquitous computing devices, the large volume and continuous flow of distributed data have imposed new constraints on the design of learning algorithms. Exploring how to extract knowledge structures from evolving and time-changing data, Knowledge Discovery from Data Streams presents


Contrast Data Mining

Contrast Data Mining

Author: Guozhu Dong

Publisher: CRC Press

Published: 2016-04-19

Total Pages: 428

ISBN-13: 1439854335

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A Fruitful Field for Researching Data Mining Methodology and for Solving Real-Life ProblemsContrast Data Mining: Concepts, Algorithms, and Applications collects recent results from this specialized area of data mining that have previously been scattered in the literature, making them more accessible to researchers and developers in data mining and


Book Synopsis Contrast Data Mining by : Guozhu Dong

Download or read book Contrast Data Mining written by Guozhu Dong and published by CRC Press. This book was released on 2016-04-19 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Fruitful Field for Researching Data Mining Methodology and for Solving Real-Life ProblemsContrast Data Mining: Concepts, Algorithms, and Applications collects recent results from this specialized area of data mining that have previously been scattered in the literature, making them more accessible to researchers and developers in data mining and


Magnetic Bubble Technology

Magnetic Bubble Technology

Author: A. H. Eschenfelder

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 328

ISBN-13: 3642965490

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Magnetic bubbles are of interest to engineers because their properties can be used for important practical electronic devices and they are of interest to physicists because their properties are manifestations of intriguing physical principles. At the same time, the fabrication of useful configurations challenges the materials scientists and engineers. A technology of magnetic bubbles has developed to the point where commercial products are being marketed. In addition, new discovery and development are driving this technology toward substantially lower costs and presumably broader application. For all of these reasons there is a need to educate newcomers to this field in universities and in industry. The purpose of this book is to provide a text for a one-semester course that can be taught under headings of Solid State Physics, Materials Science, Computer Technology or Integrated Electronics. It is expected that the student of anyone of these disciplines will be interested in each of the chapters of this book to some degree, but may concentrate on some more than others, depending on the discipline. At the end of each chapter there is a brief summary which will serve as a reminder of the contents of the chapter but can also be read ahead of time to determine the depth of your interest in the chapter.


Book Synopsis Magnetic Bubble Technology by : A. H. Eschenfelder

Download or read book Magnetic Bubble Technology written by A. H. Eschenfelder and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: Magnetic bubbles are of interest to engineers because their properties can be used for important practical electronic devices and they are of interest to physicists because their properties are manifestations of intriguing physical principles. At the same time, the fabrication of useful configurations challenges the materials scientists and engineers. A technology of magnetic bubbles has developed to the point where commercial products are being marketed. In addition, new discovery and development are driving this technology toward substantially lower costs and presumably broader application. For all of these reasons there is a need to educate newcomers to this field in universities and in industry. The purpose of this book is to provide a text for a one-semester course that can be taught under headings of Solid State Physics, Materials Science, Computer Technology or Integrated Electronics. It is expected that the student of anyone of these disciplines will be interested in each of the chapters of this book to some degree, but may concentrate on some more than others, depending on the discipline. At the end of each chapter there is a brief summary which will serve as a reminder of the contents of the chapter but can also be read ahead of time to determine the depth of your interest in the chapter.


Practical Applications of Data Mining

Practical Applications of Data Mining

Author: Sang Suh

Publisher: Jones & Bartlett Publishers

Published: 2012

Total Pages: 436

ISBN-13: 0763785873

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Introduction to data mining -- Association rules -- Classification learning -- Statistics for data mining -- Rough sets and bayes theories -- Neural networks -- Clustering -- Fuzzy information retrieval.


Book Synopsis Practical Applications of Data Mining by : Sang Suh

Download or read book Practical Applications of Data Mining written by Sang Suh and published by Jones & Bartlett Publishers. This book was released on 2012 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to data mining -- Association rules -- Classification learning -- Statistics for data mining -- Rough sets and bayes theories -- Neural networks -- Clustering -- Fuzzy information retrieval.


Data Mining and Knowledge Discovery Handbook

Data Mining and Knowledge Discovery Handbook

Author: Oded Maimon

Publisher: Springer Science & Business Media

Published: 2006-05-28

Total Pages: 1378

ISBN-13: 038725465X

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Data Mining and Knowledge Discovery Handbook organizes all major concepts, theories, methodologies, trends, challenges and applications of data mining (DM) and knowledge discovery in databases (KDD) into a coherent and unified repository. This book first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. This volume concludes with in-depth descriptions of data mining applications in various interdisciplinary industries including finance, marketing, medicine, biology, engineering, telecommunications, software, and security. Data Mining and Knowledge Discovery Handbook is designed for research scientists and graduate-level students in computer science and engineering. This book is also suitable for professionals in fields such as computing applications, information systems management, and strategic research management.


Book Synopsis Data Mining and Knowledge Discovery Handbook by : Oded Maimon

Download or read book Data Mining and Knowledge Discovery Handbook written by Oded Maimon and published by Springer Science & Business Media. This book was released on 2006-05-28 with total page 1378 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining and Knowledge Discovery Handbook organizes all major concepts, theories, methodologies, trends, challenges and applications of data mining (DM) and knowledge discovery in databases (KDD) into a coherent and unified repository. This book first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. This volume concludes with in-depth descriptions of data mining applications in various interdisciplinary industries including finance, marketing, medicine, biology, engineering, telecommunications, software, and security. Data Mining and Knowledge Discovery Handbook is designed for research scientists and graduate-level students in computer science and engineering. This book is also suitable for professionals in fields such as computing applications, information systems management, and strategic research management.


Data Warehousing and Knowledge Discovery

Data Warehousing and Knowledge Discovery

Author: Yahiko Kambayashi

Publisher: Springer

Published: 2003-05-15

Total Pages: 448

ISBN-13: 3540444661

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The Second International Conference on Data Warehousing and Knowledge Discovery (DaWaK 2000) was held in Greenwich, UK 4–6 September. DaWaK 2000 was a forum where researchers from data warehousing and knowledge discovery disciplines could exchange ideas on improving next generation decision support and data mining systems. The conference focused on the logical and physical design of data warehousing and knowledge discovery systems. The scope of the papers covered the most recent and relevant topics in the areas of data warehousing, multidimensional databases, OLAP, knowledge discovery and mining complex databases. These proceedings contain the technical papers selected for presentation at the conference. We received more than 90 papers from over 20 countries and the program committee finally selected 31 long papers and 11 short papers. The conference program included three invited talks, namely, “A Foolish Consistency: Technical Challenges in Consistency Management” by Professor Anthony Finkelstein, University College London, UK; “European Plan for Research in Data Warehousing and Knowledge Discovery” by Dr. Harald Sonnberger (Head of Unit A4, Eurostat, European Commission); and “Security in Data Warehousing” by Professor Bharat Bhargava, Purdue University, USA.


Book Synopsis Data Warehousing and Knowledge Discovery by : Yahiko Kambayashi

Download or read book Data Warehousing and Knowledge Discovery written by Yahiko Kambayashi and published by Springer. This book was released on 2003-05-15 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Second International Conference on Data Warehousing and Knowledge Discovery (DaWaK 2000) was held in Greenwich, UK 4–6 September. DaWaK 2000 was a forum where researchers from data warehousing and knowledge discovery disciplines could exchange ideas on improving next generation decision support and data mining systems. The conference focused on the logical and physical design of data warehousing and knowledge discovery systems. The scope of the papers covered the most recent and relevant topics in the areas of data warehousing, multidimensional databases, OLAP, knowledge discovery and mining complex databases. These proceedings contain the technical papers selected for presentation at the conference. We received more than 90 papers from over 20 countries and the program committee finally selected 31 long papers and 11 short papers. The conference program included three invited talks, namely, “A Foolish Consistency: Technical Challenges in Consistency Management” by Professor Anthony Finkelstein, University College London, UK; “European Plan for Research in Data Warehousing and Knowledge Discovery” by Dr. Harald Sonnberger (Head of Unit A4, Eurostat, European Commission); and “Security in Data Warehousing” by Professor Bharat Bhargava, Purdue University, USA.