计算机工程与应用Issue(17)：20-27,8.DOI:10.3778/j.issn.1002-8331.1506-0063
多标记学习研究综述
Survey on multi-label learning
摘要
Abstract
Multi-label learning, which considers the case of an object related to multiple labels, attracts much attention in recent years. Multi-label learning research aims to improve the performance of multi-label learning algorithms by reduc-ing the complexity of the feature space and the label space. This paper systematically analyses the developments in multi-label learning research from four aspects including multi-label classification, label ranking, multi-label dimension reduction and label correlation and also points out the existing problems in the multi-label learning research. Finally, it summarizes several valuable research directions, which provides reference for the further research in this field.关键词
多标记学习/分类/标记相关性/维度约简Key words
multi-label learning/classification/label correlation/dimension reduction分类
信息技术与安全科学引用本文复制引用
余鹰..多标记学习研究综述[J].计算机工程与应用,2015,(17):20-27,8.基金项目
江西省自然科学基金（No.20151BAB217011，No.20132BAB201045）；南方山地果园智能化管理技术与装备协同创新中心项目；国家自然科学基金（No.61202170，No.61462037）。 （）
