南京师大学报（自然科学版）2025，Vol.48Issue(2)：74-82,90,10.DOI:10.3969/j.issn.1001-4616.2025.02.008
多视图偏多标记分类与标记消歧的联合学习
Joint Learning of Multi-View Partial Multi-Label Classification and Label Disambiguation
摘要
Abstract
Multi-view partial multi-label learning mainly aims to deal with data with multi-view features and multiple related labels,but the label information is not completely accurate.Most of the existing methods use a two-stage approach to perform label disambiguation and multi-label classification independently,but these methods are sub-optimal.In this paper,a new learning framework of Joint Learning of Multi-View Partial Multi-Label classification and Label Disambiguation(JL-MVPML-LD)is proposed.Firstly,the multi-view features are fused by using the multi-kernel method and the importance of each view is considered.Secondly,the instance correlation and label correlation are mined and learned,and then used to help the joint learning of multi-view partial multi-label classifier and label disambiguation.Finally,JL-MVPML_LD can be solved by alternating solution method.The experimental results in 27 cases on three datasets verify the effectiveness of the proposed method.关键词
多视图偏多标记学习/核空间/标记消歧/标记相关性Key words
multi-view partial multi-label learning/kernel space/label disambiguation/label correlation分类
计算机与自动化引用本文复制引用
徐远洋,何志芬,刘彬..多视图偏多标记分类与标记消歧的联合学习[J].南京师大学报（自然科学版）,2025,48(2):74-82,90,10.基金项目
国家自然科学基金项目(62362051)、江西省自然科学基金项目(2023BAB202047). （62362051）
