Advances in Knowledge Discovery and Data Mining PDF Download
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Author: Usama M. Fayyad
Publisher:
ISBN:
Category : Computers
Languages : en
Pages : 638
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Book Description
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.
Author: Usama M. Fayyad
Publisher:
ISBN:
Category : Computers
Languages : en
Pages : 638
Get Book Here
Book Description
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.
Author: Nikhil Pal
Publisher: Springer
ISBN: 9781447157526
Category : Computers
Languages : en
Pages : 0
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Book Description
Clear and concise explanations to understand the learning paradigms. Chapters written by leading world experts.
Author: Nikhil Pal
Publisher: Springer Science & Business Media
ISBN: 1846281830
Category : Computers
Languages : en
Pages : 264
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Book Description
Clear and concise explanations to understand the learning paradigms. Chapters written by leading world experts.
Author: Krzysztof J. Cios
Publisher: Springer Science & Business Media
ISBN: 1461555892
Category : Computers
Languages : en
Pages : 508
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Book Description
Data Mining Methods for Knowledge Discovery provides an introduction to the data mining methods that are frequently used in the process of knowledge discovery. This book first elaborates on the fundamentals of each of the data mining methods: rough sets, Bayesian analysis, fuzzy sets, genetic algorithms, machine learning, neural networks, and preprocessing techniques. The book then goes on to thoroughly discuss these methods in the setting of the overall process of knowledge discovery. Numerous illustrative examples and experimental findings are also included. Each chapter comes with an extensive bibliography. Data Mining Methods for Knowledge Discovery is intended for senior undergraduate and graduate students, as well as a broad audience of professionals in computer and information sciences, medical informatics, and business information systems.
Author: O. Maimon
Publisher: Springer Science & Business Media
ISBN: 9780792366478
Category : Computers
Languages : en
Pages : 192
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Book Description
This book presents a specific and unified approach to Knowledge Discovery and Data Mining, termed IFN for Information Fuzzy Network methodology. Data Mining (DM) is the science of modelling and generalizing common patterns from large sets of multi-type data. DM is a part of KDD, which is the overall process for Knowledge Discovery in Databases. The accessibility and abundance of information today makes this a topic of particular importance and need. The book has three main parts complemented by appendices as well as software and project data that are accessible from the book's web site (http://www.eng.tau.ac.iV-maimonlifn-kdg£). Part I (Chapters 1-4) starts with the topic of KDD and DM in general and makes reference to other works in the field, especially those related to the information theoretic approach. The remainder of the book presents our work, starting with the IFN theory and algorithms. Part II (Chapters 5-6) discusses the methodology of application and includes case studies. Then in Part III (Chapters 7-9) a comparative study is presented, concluding with some advanced methods and open problems. The IFN, being a generic methodology, applies to a variety of fields, such as manufacturing, finance, health care, medicine, insurance, and human resources. The appendices expand on the relevant theoretical background and present descriptions of sample projects (including detailed results).
Author: David L. Olson
Publisher: Springer Science & Business Media
ISBN: 354076917X
Category : Business & Economics
Languages : en
Pages : 182
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Book Description
This book covers the fundamental concepts of data mining, to demonstrate the potential of gathering large sets of data, and analyzing these data sets to gain useful business understanding. The book is organized in three parts. Part I introduces concepts. Part II describes and demonstrates basic data mining algorithms. It also contains chapters on a number of different techniques often used in data mining. Part III focuses on business applications of data mining.
Author: Francesco Bonchi
Publisher: CRC Press
ISBN: 1439803668
Category : Computers
Languages : en
Pages : 527
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Book Description
Covering research at the frontier of this field, Privacy-Aware Knowledge Discovery: Novel Applications and New Techniques presents state-of-the-art privacy-preserving data mining techniques for application domains, such as medicine and social networks, that face the increasing heterogeneity and complexity of new forms of data. Renowned authorities
Author: Harvey J. Miller
Publisher: CRC Press
ISBN: 1420073982
Category : Computers
Languages : en
Pages : 488
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Book Description
The Definitive Volume on Cutting-Edge Exploratory Analysis of Massive Spatial and Spatiotemporal DatabasesSince the publication of the first edition of Geographic Data Mining and Knowledge Discovery, new techniques for geographic data warehousing (GDW), spatial data mining, and geovisualization (GVis) have been developed. In addition, there has bee
Author: Oded Maimon
Publisher: Springer Science & Business Media
ISBN: 038725465X
Category : Computers
Languages : en
Pages : 1378
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Book Description
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.
Author: Krzysztof J. Cios
Publisher: Springer Science & Business Media
ISBN: 0387367950
Category : Computers
Languages : en
Pages : 601
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Book Description
This comprehensive textbook on data mining details the unique steps of the knowledge discovery process that prescribes the sequence in which data mining projects should be performed, from problem and data understanding through data preprocessing to deployment of the results. This knowledge discovery approach is what distinguishes Data Mining from other texts in this area. The book provides a suite of exercises and includes links to instructional presentations. Furthermore, it contains appendices of relevant mathematical material.
