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Preference Learning

Editors: Fürnkranz, Johannes, Hüllermeier, Eyke (Eds.)

  • This is the first book dedicated to this topic
  • This topic has attracted considerable attention in artificial intelligence research in recent years
  • A comprehensive treatment
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eBook $139.00
price for USA
  • ISBN 978-3-642-14125-6
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Download immediately after purchase
Hardcover $179.00
price for USA
  • ISBN 978-3-642-14124-9
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $179.00
price for USA
  • ISBN 978-3-642-42230-0
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this book

The topic of preferences is a new branch of machine learning and data mining, and it has attracted considerable attention in artificial intelligence research in recent years. Representing and processing knowledge in terms of preferences is appealing as it allows one to specify desires in a declarative way, to combine qualitative and quantitative modes of reasoning, and to deal with inconsistencies and exceptions in a flexible manner. Preference learning is concerned with the acquisition of preference models from data – it involves learning from observations that reveal information about the preferences of an individual or a class of individuals, and building models that generalize beyond such training data. This is the first book dedicated to this topic, and the treatment is comprehensive. The editors first offer a thorough introduction, including a systematic categorization according to learning task and learning technique, along with a unified notation. The remainder of the book is organized into parts that follow the developed framework, complementing survey articles with in-depth treatises of current research topics in this area. The book will be of interest to researchers and practitioners in artificial intelligence, in particular machine learning and data mining, and in fields such as multicriteria decision-making and operations research.

Reviews

From the reviews:

“The book looks at three major types of preference learning: label ranking, instance ranking, and object ranking. … chapters contain case studies and actual experiments to illustrate the claims made within. … this is a useful book in an emerging and important area, and hence would be of interest to machine learning researchers. The book is quite readable to that audience, despite a heavy emphasis on formal treatment.” (M. Sasikumar, ACM Computing Reviews, September, 2011)


Table of contents (20 chapters)

  • Preference Learning: An Introduction

    Fürnkranz, Johannes (et al.)

    Pages 1-17

  • A Preference Optimization Based Unifying Framework for Supervised Learning Problems

    Aiolli, Fabio (et al.)

    Pages 19-42

  • Label Ranking Algorithms: A Survey

    Vembu, Shankar (et al.)

    Pages 45-64

  • Preference Learning and Ranking by Pairwise Comparison

    Fürnkranz, Johannes (et al.)

    Pages 65-82

  • Decision Tree Modeling for Ranking Data

    Yu, Philip L. H. (et al.)

    Pages 83-106

Buy this book

eBook $139.00
price for USA
  • ISBN 978-3-642-14125-6
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Download immediately after purchase
Hardcover $179.00
price for USA
  • ISBN 978-3-642-14124-9
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $179.00
price for USA
  • ISBN 978-3-642-42230-0
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Preference Learning
Editors
  • Johannes Fürnkranz
  • Eyke Hüllermeier
Copyright
2011
Publisher
Springer-Verlag Berlin Heidelberg
Copyright Holder
Springer-Verlag Berlin Heidelberg
eBook ISBN
978-3-642-14125-6
DOI
10.1007/978-3-642-14125-6
Hardcover ISBN
978-3-642-14124-9
Softcover ISBN
978-3-642-42230-0
Edition Number
1
Number of Pages
IX, 466
Topics