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Titlebook: Relational Data Mining; Sa?o D?eroski,Nada Lavra? Book 2001 Springer-Verlag Berlin Heidelberg 2001 Algorithmic Learning.Data Analysis.Data

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書目名稱Relational Data Mining
編輯Sa?o D?eroski,Nada Lavra?
視頻videohttp://file.papertrans.cn/827/826091/826091.mp4
概述The first book on Relational Data Mining.Includes supplementary material:
圖書封面Titlebook: Relational Data Mining;  Sa?o D?eroski,Nada Lavra? Book 2001 Springer-Verlag Berlin Heidelberg 2001 Algorithmic Learning.Data Analysis.Data
描述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.
出版日期Book 2001
關(guān)鍵詞Algorithmic Learning; Data Analysis; Data Mining; Inductive Logic Programming; Knowledge Discovery; Knowl
版次1
doihttps://doi.org/10.1007/978-3-662-04599-2
isbn_softcover978-3-642-07604-6
isbn_ebook978-3-662-04599-2
copyrightSpringer-Verlag Berlin Heidelberg 2001
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Knowledge Discovery in Databases: An Overviewn support databases where analysis and exploration operations are essential. Inductive logic programming can potentially play some key roles in KDD. We define the basic notions in data mining and KDD, define the goals, present motivation, and give a high-level definition of the KDD Process and how i
地板
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An Introduction to Inductive Logic Programmingth data stored in multiple tables, ILP systems are usually able to take into account generally valid background (domain) knowledge in the form of a logic program. They also use the powerful language of logic programs for describing discovered patterns. This chapter introduces the basics of logic pro
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Inductive Logic Programming for Knowledge Discovery in Databasesl databases. This reduces the need for manual preprocessing and allows problems to be treated that cannot be handled easily with standard single-table methods. This paper provides a tutorial-style introduction to the topic, beginning with a detailed explanation of why and where one might be interest
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Relational Rule Induction with CP,4.4: A Tutorial Introductionource code, the reader is guided through the development of Progol input files containing type definitions, mode declarations, background knowledge, examples and integrity constraints. The theory behind the system is then described using a simple example as illustration. The main algorithms in . are
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