Synopsis
Preference Learning: An Introduction.- A Preference Optimization Based Unifying Framework for Supervised Learning Problems.- Label Ranking Algorithms: A Survey.- Preference Learning and Ranking by Pairwise Comparison.- Decision Tree Modeling for Ranking Data.- Co-regularized Least-Squares for Label Ranking.- A Survey on ROC-Based Ordinal Regression.- Ranking Cases with Classification Rules.- A Survey and Empirical Comparison of Object Ranking Methods.- Dimension Reduction for Object Ranking.- Learning of Rule Ensembles for Multiple Attribute Ranking Problems.- Learning Lexicographic Preference Models.- Learning Ordinal Preferences on Multiattribute Domains: the Case of CP-nets.- Choice-Based Conjoint Analysis: Classification vs. Discrete Choice Models.- Learning Aggregation Operators for Preference Modeling.- Evaluating Search Engine Relevance with Click-Based Metrics.- Learning SVM Ranking Function from User Feedback Using Document.- Metadata and Active Learning in the Biomedical Domain.- Learning Preference Models in Recommender Systems.- Collaborative Preference Learning.- Discerning Relevant Model Features in a Content-Based Collaborative Recommender System.- Author Index.- Subject Index
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