@inbook{aae03b313e7c4b62b367ebb032978084,
title = "Label ranking: a new rule-based label ranking method",
abstract = "This work focuses on a particular application of preference ranking, wherein the problem is to learn a mapping from instances to rankings over a finite set of labels, i.e. label ranking. Our approach is based on a learning reduction technique and provides such a mapping in the form of logical rules: if [antecedent] then [consequent], where [antecedent] contains a set of conditions, usually connected by a logical conjunction operator (AND) while [consequent] consists in a ranking among labels. The approach presented in this paper mainly comprises five phases: preprocessing, rules generation, post-processing, classification and ranking generation.",
author = "M. Gurrieri and X. Siebert and P. Fortemps and Salvatore Greco and R. S{\l}owi{\'n}ski",
year = "2012",
doi = "10.1007/978-3-642-31709-5_62",
language = "English",
isbn = "9783642317088",
volume = "297",
series = "Communications in computer and information science",
publisher = "Springer",
number = "297",
pages = "613--623",
editor = "Salvatore Greco and B. Bouchon-Meunier and G. Coletti and M. Fedrizzi and B. Matarazzo and R. Yager",
booktitle = "Advances on computational intelligence: 14th international conference on information processing and management of uncertainty in knowledge-based systems, proceedings, part 1",
edition = "297",
}