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

DOWNLOAD EBOOK

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.

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

DOWNLOAD EBOOK

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 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

DOWNLOAD EBOOK

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.

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

DOWNLOAD EBOOK

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

Urban Informatics
Urban Informatics

Author: Wenzhong Shi

Publisher: Springer Nature

Published: 2021-04-06

Total Pages: 941

ISBN-13: 9811589836

DOWNLOAD EBOOK

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity.

Advances in Knowledge Discovery and Data Mining
Advances in Knowledge Discovery and Data Mining

Author: Usama M. Fayyad

Publisher:

Published: 1996

Total Pages: 638

ISBN-13:

DOWNLOAD EBOOK

Eight sections of this book span fundamental issues of knowledge discovery, classification and clustering, trend and deviation analysis, dependency derivation, integrated discovery systems, augumented database systems and application case studies. The appendices provide a list of terms used in the literature of the field of data mining and knowledge discovery in databases, and a list of online resources for the KDD researcher.

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

DOWNLOAD EBOOK

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.

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

DOWNLOAD EBOOK

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.

Contrast Data Mining
Contrast Data Mining

Author: Guozhu Dong

Publisher: CRC Press

Published: 2016-04-19

Total Pages: 428

ISBN-13: 1439854335

DOWNLOAD EBOOK

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