Fürnkranz, Johannes

Preference Learning

Fürnkranz, Johannes - Preference Learning, ebook


Ebook, PDF with Adobe DRM
ISBN: 9783642141256
DRM Restrictions

PrintingNot allowed
Copy to clipboardNot allowed

Table of contents

1. Preference Learning: An Introduction
Johannes Fürnkranz, Eyke Hüllermeier

2. A Preference Optimization Based Unifying Framework for Supervised Learning Problems
Fabio Aiolli, Alessandro Sperduti

3. Label Ranking Algorithms: A Survey
Shankar Vembu, Thomas Gärtner

4. Preference Learning and Ranking by Pairwise Comparison
Johannes Fürnkranz, Eyke Hüllermeier

5. Decision Tree Modeling for Ranking Data
Philip L. H. Yu, Wai Ming Wan, Paul H. Lee

6. Co-Regularized Least-Squares for Label Ranking
Evgeni Tsivtsivadze, Tapio Pahikkala, Jorma Boberg, Tapio Salakoski, Tom Heskes

7. A Survey on ROC-based Ordinal Regression
Willem Waegeman, Bernard De Baets

8. Ranking Cases with Classification Rules
Jianping Zhang, Jerzy W. Bala, Ali Hadjarian, Brent Han

9. A Survey and Empirical Comparison of Object Ranking Methods
Toshihiro Kamishima, Hideto Kazawa, Shotaro Akaho

10. Dimension Reduction for Object Ranking
Toshihiro Kamishima, Shotaro Akaho

11. Learning of Rule Ensembles for Multiple Attribute Ranking Problems
Krzysztof Dembczyński, Wojciech Kotłowski, Roman Słowiński, Marcin Szeląg

12. Learning Lexicographic Preference Models
Fusun Yaman, Thomas J. Walsh, Michael L. Littman, Marie desJardins

13. Learning Ordinal Preferences on Multiattribute Domains: The Case of CP-nets
Yann Chevaleyre, Frédéric Koriche, Jérôme Lang, Jérôme Mengin, Bruno Zanuttini

14. Choice-Based Conjoint Analysis: Classification vs. Discrete Choice Models
Joachim Giesen, Klaus Mueller, Bilyana Taneva, Peter Zolliker

15. Learning Aggregation Operators for Preference Modeling
Vicenç Torra

16. Evaluating Search Engine Relevance with Click-Based Metrics
Filip Radlinski, Madhu Kurup, Thorsten Joachims

17. Learning SVM Ranking Functions from User Feedback Using Document Metadata and Active Learning in the Biomedical Domain
Robert Arens

18. Learning Preference Models in Recommender Systems
Marco de Gemmis, Leo Iaquinta, Pasquale Lops, Cataldo Musto, Fedelucio Narducci, Giovanni Semeraro

19. Collaborative Preference Learning
Alexandros Karatzoglou, Markus Weimer

20. Discerning Relevant Model Features in a Content-based Collaborative Recommender System
Alejandro Bellogín, Iván Cantador, Pablo Castells, Álvaro Ortigosa

Keywords: Computer Science, Artificial Intelligence (incl. Robotics), Data Mining and Knowledge Discovery

Publication year
Information Technology, Telecommunications

Similar titles