Relational Data Mining

Relational Data Mining PDF Author: Saso Dzeroski
Publisher: Springer Science & Business Media
ISBN: 9783540422891
Category : Business & Economics
Languages : en
Pages : 422

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Book Description
As the first book devoted to relational data mining, this coherently written multi-author monograph provides a thorough introduction and systematic overview of the area. The first part introduces the reader to the basics and principles of classical knowledge discovery in databases and inductive logic programming; subsequent chapters by leading experts assess the techniques in relational data mining in a principled and comprehensive way; finally, three chapters deal with advanced applications in various fields and refer the reader to resources for relational data mining. This book will become a valuable source of reference for R&D professionals active in relational data mining. Students as well as IT professionals and ambitioned practitioners interested in learning about relational data mining will appreciate the book as a useful text and gentle introduction to this exciting new field.

Relational Data Mining

Relational Data Mining PDF Author: Saso Dzeroski
Publisher: Springer Science & Business Media
ISBN: 9783540422891
Category : Business & Economics
Languages : en
Pages : 422

Get Book Here

Book Description
As the first book devoted to relational data mining, this coherently written multi-author monograph provides a thorough introduction and systematic overview of the area. The first part introduces the reader to the basics and principles of classical knowledge discovery in databases and inductive logic programming; subsequent chapters by leading experts assess the techniques in relational data mining in a principled and comprehensive way; finally, three chapters deal with advanced applications in various fields and refer the reader to resources for relational data mining. This book will become a valuable source of reference for R&D professionals active in relational data mining. Students as well as IT professionals and ambitioned practitioners interested in learning about relational data mining will appreciate the book as a useful text and gentle introduction to this exciting new field.

Knowledge Discovery in Inductive Databases

Knowledge Discovery in Inductive Databases PDF Author: Saso Dzeroski
Publisher: Springer
ISBN: 3540755497
Category : Computers
Languages : en
Pages : 310

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Book Description
This book constitutes the thoroughly refereed joint postproceedings of the 5th International Workshop on Knowledge Discovery in Inductive Databases, KDID 2006, held in association with ECML/PKDD. Bringing together the fields of databases, machine learning, and data mining, the papers address various current topics in knowledge discovery and data mining in the framework of inductive databases such as constraint-based mining, database technology and inductive querying.

Knowledge Discovery in Inductive Databases

Knowledge Discovery in Inductive Databases PDF Author: Francesco Bonchi
Publisher: Springer
ISBN: 3540332936
Category : Computers
Languages : en
Pages : 259

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Book Description
This book presents the thoroughly refereed joint postproceedings of the 4th International Workshop on Knowledge Discovery in Inductive Databases, October 2005. 20 revised full papers presented together with 2 are reproduced here. Bringing together the fields of databases, machine learning, and data mining, the papers address various current topics in knowledge discovery and data mining in the framework of inductive databases such as constraint-based mining, database technology and inductive querying.

Data Warehousing and Knowledge Discovery

Data Warehousing and Knowledge Discovery PDF Author: Mukesh Mohania
Publisher: Springer Science & Business Media
ISBN: 3540664580
Category : Business & Economics
Languages : en
Pages : 413

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Book Description
This book constitutes the refereed proceedings of the First International Conference on Data Warehousing and Knowledge Discovery, DaWaK'99, held in Florence, Italy in August/September 1999. The 31 revised full papers and nine short papers presented were carefully reviewed and selected from 88 submissions. The book is divided in topical sections on data warehouse design; online analytical processing; view synthesis, selection, and optimization; multidimensional databases; knowledge discovery; association rules; inexing and object similarities; generalized association rules and data and web mining; time series data bases; data mining applications and data analysis.

Principles of Data Mining and Knowledge Discovery

Principles of Data Mining and Knowledge Discovery PDF Author: Jan Zytkow
Publisher: Springer Science & Business Media
ISBN: 3540664904
Category : Computers
Languages : en
Pages : 608

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Book Description
This book constitutes the refereed proceedings of the Third European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD'99, held in Prague, Czech Republic in September 1999. The 28 revised full papers and 48 poster presentations were carefully reviewed and selected from 106 full papers submitted. The papers are organized in topical sections on time series, applications, taxonomies and partitions, logic methods, distributed and multirelational databases, text mining and feature selection, rules and induction, and interesting and unusual issues.

Advances in Knowledge Discovery and Data Mining

Advances in Knowledge Discovery and Data Mining PDF 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.

Relational Knowledge Discovery

Relational Knowledge Discovery PDF Author: M. E. Müller
Publisher: Cambridge University Press
ISBN: 0521190215
Category : Computers
Languages : en
Pages : 279

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Book Description
Introductory textbook presenting relational methods in machine learning.

Knowledge Discovery in Inductive Databases

Knowledge Discovery in Inductive Databases PDF Author:
Publisher:
ISBN:
Category : Data mining
Languages : en
Pages : 276

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Book Description


Privacy-Aware Knowledge Discovery

Privacy-Aware Knowledge Discovery PDF 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

Knowledge Discovery in Multiple Databases

Knowledge Discovery in Multiple Databases PDF Author: Shichao Zhang
Publisher: Springer Science & Business Media
ISBN: 9781852337032
Category : Computers
Languages : en
Pages : 250

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Book Description
The Web has emerged as a large, distributed data repository, and information on the Internet and in existing transaction databases can be analyzed for commercial gains in decision making. Therefore, how to efficiently identify quality knowledge from different data sources uncovers a significant challenge. This challenge has attracted wide interest from both academia and the industry. Knowledge Discovery in Multiple Databases provides a comprehensive introduction to the latest advancements in multi-database mining, and presents a local-pattern analysis framework for pattern discovery from multiple data sources. Based on this framework, data preparation techniques in multiple databases, an application-independent database classification for data reduction, and efficient algorithms for pattern discovery from multiple databases are described. Knowledge Discovery in Multiple Databases is suitable for researchers, professionals and students in data mining, distributed data analysis, and machine learning, who are interested in multi-database mining. It is also appropriate for use as a text supplement for broader courses that might involve knowledge discovery in databases and data mining.