Knowledge Discovery In Databases Pkdd 2006
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Knowledge Discovery In Databases Pkdd 2006
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Author : Johannes Fürnkranz
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-09-15
Knowledge Discovery In Databases Pkdd 2006 written by Johannes Fürnkranz and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-09-15 with Computers categories.
This book constitutes the refereed proceedings of the 10th European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD 2006. The book presents 36 revised full papers and 26 revised short papers together with abstracts of 5 invited talks, carefully reviewed and selected from 564 papers submitted. The papers offer a wealth of new results in knowledge discovery in databases and address all current issues in the area.
Knowledge Discovery In Databases
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Author :
language : en
Publisher:
Release Date : 2006
Knowledge Discovery In Databases written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Data mining categories.
Privacy Preserving Data Mining
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Author : Jaideep Vaidya
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-11-29
Privacy Preserving Data Mining written by Jaideep Vaidya and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-11-29 with Computers categories.
Privacy preserving data mining implies the "mining" of knowledge from distributed data without violating the privacy of the individual/corporations involved in contributing the data. This volume provides a comprehensive overview of available approaches, techniques and open problems in privacy preserving data mining. Crystallizing much of the underlying foundation, the book aims to inspire further research in this new and growing area. Privacy Preserving Data Mining is intended to be accessible to industry practitioners and policy makers, to help inform future decision making and legislation, and to serve as a useful technical reference.
Knowledge Discovery In Databases Pkdd 2006
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Author : Johannes Fürnkranz
language : en
Publisher: Springer
Release Date : 2009-09-02
Knowledge Discovery In Databases Pkdd 2006 written by Johannes Fürnkranz and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-09-02 with Computers categories.
This book constitutes the refereed proceedings of the 10th European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD 2006. The book presents 36 revised full papers and 26 revised short papers together with abstracts of 5 invited talks, carefully reviewed and selected from 564 papers submitted. The papers offer a wealth of new results in knowledge discovery in databases and address all current issues in the area.
Machine Learning And Knowledge Discovery In Databases
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Author : Walter Daelemans
language : en
Publisher: Springer
Release Date : 2008-08-17
Machine Learning And Knowledge Discovery In Databases written by Walter Daelemans and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-08-17 with Computers categories.
This book constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2008, held in Antwerp, Belgium, in September 2008. The 100 papers presented in two volumes, together with 5 invited talks, were carefully reviewed and selected from 521 submissions. In addition to the regular papers the volume contains 14 abstracts of papers appearing in full version in the Machine Learning Journal and the Knowledge Discovery and Databases Journal of Springer. The conference intends to provide an international forum for the discussion of the latest high quality research results in all areas related to machine learning and knowledge discovery in databases. The topics addressed are application of machine learning and data mining methods to real-world problems, particularly exploratory research that describes novel learning and mining tasks and applications requiring non-standard techniques.
Knowledge Discovery In Databases Pkdd 2007
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Author : Joost N. Kok
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-08-31
Knowledge Discovery In Databases Pkdd 2007 written by Joost N. Kok and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-08-31 with Computers categories.
This book constitutes the refereed proceedings of the 11th European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD 2007, held in Warsaw, Poland, co-located with ECML 2007, the 18th European Conference on Machine Learning. The 28 revised full papers and 35 revised short papers present original results on leading-edge subjects of knowledge discovery from conventional and complex data and address all current issues in the area.
Metalearning
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Author : Pavel Brazdil
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-11-26
Metalearning written by Pavel Brazdil and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-11-26 with Computers categories.
Metalearning is the study of principled methods that exploit metaknowledge to obtain efficient models and solutions by adapting machine learning and data mining processes. While the variety of machine learning and data mining techniques now available can, in principle, provide good model solutions, a methodology is still needed to guide the search for the most appropriate model in an efficient way. Metalearning provides one such methodology that allows systems to become more effective through experience. This book discusses several approaches to obtaining knowledge concerning the performance of machine learning and data mining algorithms. It shows how this knowledge can be reused to select, combine, compose and adapt both algorithms and models to yield faster, more effective solutions to data mining problems. It can thus help developers improve their algorithms and also develop learning systems that can improve themselves. The book will be of interest to researchers and graduate students in the areas of machine learning, data mining and artificial intelligence.
Comparative Analysis Of Deterministic And Nondeterministic Decision Trees
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Author : Mikhail Moshkov
language : en
Publisher: Springer Nature
Release Date : 2020-03-14
Comparative Analysis Of Deterministic And Nondeterministic Decision Trees written by Mikhail Moshkov and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-14 with Technology & Engineering categories.
This book compares four parameters of problems in arbitrary information systems: complexity of problem representation and complexity of deterministic, nondeterministic, and strongly nondeterministic decision trees for problem solving. Deterministic decision trees are widely used as classifiers, as a means of knowledge representation, and as algorithms. Nondeterministic (strongly nondeterministic) decision trees can be interpreted as systems of true decision rules that cover all objects (objects from one decision class). This book develops tools for the study of decision trees, including bounds on complexity and algorithms for construction of decision trees for decision tables with many-valued decisions. It considers two approaches to the investigation of decision trees for problems in information systems: local, when decision trees can use only attributes from the problem representation; and global, when decision trees can use arbitrary attributes from the information system. For both approaches, it describes all possible types of relationships among the four parameters considered and discusses the algorithmic problems related to decision tree optimization. The results presented are useful for researchers who apply decision trees and rules to algorithm design and to data analysis, especially those working in rough set theory, test theory and logical analysis of data. This book can also be used as the basis for graduate courses.
Pattern Mining With Evolutionary Algorithms
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Author : Sebastián Ventura
language : en
Publisher: Springer
Release Date : 2016-06-13
Pattern Mining With Evolutionary Algorithms written by Sebastián Ventura and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-06-13 with Computers categories.
This book provides a comprehensive overview of the field of pattern mining with evolutionary algorithms. To do so, it covers formal definitions about patterns, patterns mining, type of patterns and the usefulness of patterns in the knowledge discovery process. As it is described within the book, the discovery process suffers from both high runtime and memory requirements, especially when high dimensional datasets are analyzed. To solve this issue, many pruning strategies have been developed. Nevertheless, with the growing interest in the storage of information, more and more datasets comprise such a dimensionality that the discovery of interesting patterns becomes a challenging process. In this regard, the use of evolutionary algorithms for mining pattern enables the computation capacity to be reduced, providing sufficiently good solutions. This book offers a survey on evolutionary computation with particular emphasis on genetic algorithms and genetic programming. Also included is an analysis of the set of quality measures most widely used in the field of pattern mining with evolutionary algorithms. This book serves as a review of the most important evolutionary algorithms for pattern mining. It considers the analysis of different algorithms for mining different type of patterns and relationships between patterns, such as frequent patterns, infrequent patterns, patterns defined in a continuous domain, or even positive and negative patterns. A completely new problem in the pattern mining field, mining of exceptional relationships between patterns, is discussed. In this problem the goal is to identify patterns which distribution is exceptionally different from the distribution in the complete set of data records. Finally, the book deals with the subgroup discovery task, a method to identify a subgroup of interesting patterns that is related to a dependent variable or target attribute. This subgroup of patterns satisfies two essential conditions: interpretability and interestingness.
Applications Of Declarative Programming And Knowledge Management
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Author : Dietmar Seipel
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-04-22
Applications Of Declarative Programming And Knowledge Management written by Dietmar Seipel and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-04-22 with Computers categories.
knowledgewrappedinrules,databases,ortheWeballowsonetoexploreintere- ing hidden knowledge.Declarativetechniques for the transformation,deduction, induction, visualization, or querying of knowledge, or data mining techniques for exploring knowledge have the advantage of high transparency and better maintainability compared to procedural approaches.