【摘要】 提出一种新型的利用多视图树的方法解决多关系分类的问题。在多视图分类方法中,不同视图对分类任务贡献不同,视图间存在互补性。对视图互补性进行研究,提出视图互补性的度量方法。根据视图互补性选择视图进行集成,构造多视图树,用于多关系分类。实验结果表明,多视图树无论在分类效果还是效率上,都优于现有的多关系分类方法。更多还原

【Abstract】 In this paper,a new approach using multiple view tree is proposed to solve the problem of multi-relational classification.In the multiple view classification,different individual view has different contribution to the classification task.Views are complementary to the classification.The complementary property of views is studies and a compute method of views is proposed complementary.The views are chosen to integrate to construct a multi-view tree according to the views complementary.Experimental results show that multi-relational classification method based on multiple view tree outperforms the existing methods in terms of accuracy and efficiency.更多还原