计算机工程与应用 ›› 2015, Vol. 51 ›› Issue (17): 20-27.

• 博士论坛 • 上一篇    下一篇

多标记学习研究综述

余  鹰   

  1. 华东交通大学 软件学院,南昌 330013
  • 出版日期:2015-09-01 发布日期:2015-09-14

Survey on multi-label learning

YU Ying   

  1. School of Software, East China Jiaotong University, Nanchang 330013, China
  • Online:2015-09-01 Published:2015-09-14

摘要: 多标记学习考虑一个对象与多个类别标记相关联的情况,是当前国际机器学习领域研究的热点问题之一。多标记学习的研究主要围绕降低特征空间和标记空间的复杂性,提高多标记学习算法的精度而展开。针对这一特点,从多标记分类、标记排序、多标记维度约简和标记相关性分析四个方面,对多标记学习的研究进展进行了归纳与阐述,分析了当前多标记学习存在的问题。最后指出了目前多标记学习若干发展方向,为该领域的进一步研究提供参考。

关键词: 多标记学习, 分类, 标记相关性, 维度约简

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 reducing 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.

Key words: multi-label learning, classification, label correlation, dimension reduction