Preference Learning

Chapter 1 Preference Learning: An Introduction

Chapter 2 A Preference Optimization Based Unifying Framework for Supervised Learning Problems

Chapter 3 Label Ranking Algorithms: A Survey

Chapter 4 Preference Learning and Ranking by Pairwise Comparison

Chapter 5 Decision Tree Modeling for Ranking Data

Chapter 6 Co-Regularized Least-Squares for Label Ranking

Chapter 7 A Survey on ROC-based Ordinal Regression

Chapter 8 Ranking Cases with Classification Rules

Chapter 9 A Survey and Empirical Comparison of Object Ranking Methods

Chapter 10 Dimension Reduction for Object Ranking

Chapter 11 Learning of Rule Ensembles for Multiple Attribute Ranking Problems

Chapter 12 Learning Lexicographic Preference Models

Chapter 13 Learning Ordinal Preferences on Multiattribute Domains: The Case of CP-nets

Chapter 15 Learning Aggregation Operators for Preference Modeling

Chapter 16 Evaluating Search Engine Relevance with Click-Based Metrics

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

Chapter 18 Learning Preference Models in Recommender Systems

Chapter 19 Collaborative Preference Learning

Chapter 20 Discerning Relevant Model Features in a Content-based Collaborative Recommender System