Knowledge-Oriented Applications in Data Mining
Knowledge-Oriented Applications in Data Mining

Author: Kimito Funatsu

Publisher: BoD – Books on Demand

Published: 2011-01-21

Total Pages: 458

ISBN-13: 9533071540

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The progress of data mining technology and large public popularity establish a need for a comprehensive text on the subject. The series of books entitled by 'Data Mining' address the need by presenting in-depth description of novel mining algorithms and many useful applications. In addition to understanding each section deeply, the two books present useful hints and strategies to solving problems in the following chapters. The contributing authors have highlighted many future research directions that will foster multi-disciplinary collaborations and hence will lead to significant development in the field of data mining.

Optimization Based Data Mining: Theory and Applications
Optimization Based Data Mining: Theory and Applications

Author: Yong Shi

Publisher: Springer Science & Business Media

Published: 2011-05-16

Total Pages: 314

ISBN-13: 0857295047

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Optimization techniques have been widely adopted to implement various data mining algorithms. In addition to well-known Support Vector Machines (SVMs) (which are based on quadratic programming), different versions of Multiple Criteria Programming (MCP) have been extensively used in data separations. Since optimization based data mining methods differ from statistics, decision tree induction, and neural networks, their theoretical inspiration has attracted many researchers who are interested in algorithm development of data mining. Optimization based Data Mining: Theory and Applications, mainly focuses on MCP and SVM especially their recent theoretical progress and real-life applications in various fields. These include finance, web services, bio-informatics and petroleum engineering, which has triggered the interest of practitioners who look for new methods to improve the results of data mining for knowledge discovery. Most of the material in this book is directly from the research and application activities that the authors’ research group has conducted over the last ten years. Aimed at practitioners and graduates who have a fundamental knowledge in data mining, it demonstrates the basic concepts and foundations on how to use optimization techniques to deal with data mining problems.

Data Mining Applications for Empowering Knowledge Societies
Data Mining Applications for Empowering Knowledge Societies

Author: Rahman, Hakikur

Publisher: IGI Global

Published: 2008-07-31

Total Pages: 356

ISBN-13: 1599046598

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Presents an overview of the main issues of data mining, including its classification, regression, clustering, and ethical issues. Provides readers with knowledge enhancing processes as well as a wide spectrum of data mining applications.

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.

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.

Knowledge Discovery Practices and Emerging Applications of Data Mining: Trends and New Domains
Knowledge Discovery Practices and Emerging Applications of Data Mining: Trends and New Domains

Author: Kumar, A.V. Senthil

Publisher: IGI Global

Published: 2010-08-31

Total Pages: 414

ISBN-13: 160960069X

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Knowledge Discovery Practices and Emerging Applications of Data Mining: Trends and New Domains introduces the reader to recent research activities in the field of data mining. This book covers association mining, classification, mobile marketing, opinion mining, microarray data mining, internet mining and applications of data mining on biological data, telecommunication and distributed databases, among others, while promoting understanding and implementation of data mining techniques in emerging domains.

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.

Introduction to Data Mining and its Applications
Introduction to Data Mining and its Applications

Author: S. Sumathi

Publisher: Springer

Published: 2006-10-12

Total Pages: 836

ISBN-13: 3540343512

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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.

Discovering Knowledge in Data
Discovering Knowledge in Data

Author: Daniel T. Larose

Publisher: John Wiley & Sons

Published: 2005-01-28

Total Pages: 240

ISBN-13: 0471687537

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Learn Data Mining by doing data mining Data mining can be revolutionary-but only when it's done right. The powerful black box data mining software now available can produce disastrously misleading results unless applied by a skilled and knowledgeable analyst. Discovering Knowledge in Data: An Introduction to Data Mining provides both the practical experience and the theoretical insight needed to reveal valuable information hidden in large data sets. Employing a "white box" methodology and with real-world case studies, this step-by-step guide walks readers through the various algorithms and statistical structures that underlie the software and presents examples of their operation on actual large data sets. Principal topics include: * Data preprocessing and classification * Exploratory analysis * Decision trees * Neural and Kohonen networks * Hierarchical and k-means clustering * Association rules * Model evaluation techniques Complete with scores of screenshots and diagrams to encourage graphical learning, Discovering Knowledge in Data: An Introduction to Data Mining gives students in Business, Computer Science, and Statistics as well as professionals in the field the power to turn any data warehouse into actionable knowledge. An Instructor's Manual presenting detailed solutions to all the problems in the book is available online.

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.