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Logical and Relational Learning
Hardback

Logical and Relational Learning

$130.99
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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.

This book constitutes the first textbook on inductive logic programming (ILP) and multi-relational data mining (MRDM). These subfields of data mining and machine learning are concerned with analyzing structured data that arise in numerous applications, such as bioinformatics, web mining, natural language processing, etc. The book explains some important techniques in detail by using case studies centered around well-known ILP or MRDM systems. These case studies are some of the classics of the field and also provide an adequate starting point for a more general discussion. Related systems and techniques are covered in a bibliographical section at the end of each chapter.The book addresses graduate students in computer science, data bases and artificial intelligence as well as practitioners of data mining and machine learning.

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MORE INFO
Format
Hardback
Publisher
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Country
Germany
Date
12 September 2008
Pages
387
ISBN
9783540200406

This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.

This book constitutes the first textbook on inductive logic programming (ILP) and multi-relational data mining (MRDM). These subfields of data mining and machine learning are concerned with analyzing structured data that arise in numerous applications, such as bioinformatics, web mining, natural language processing, etc. The book explains some important techniques in detail by using case studies centered around well-known ILP or MRDM systems. These case studies are some of the classics of the field and also provide an adequate starting point for a more general discussion. Related systems and techniques are covered in a bibliographical section at the end of each chapter.The book addresses graduate students in computer science, data bases and artificial intelligence as well as practitioners of data mining and machine learning.

Read More
Format
Hardback
Publisher
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Country
Germany
Date
12 September 2008
Pages
387
ISBN
9783540200406