使用标签关联的多标签分类

2015 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM) Pub Date : 2015-11-30 DOI:10.1109/PACRIM.2015.7334815

Yuichiro Kase, T. Miura

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引用次数: 1

摘要

在本研究中，我们讨论了一个多标签分类问题，其中文档可能有多个标签。我们以概率的方式关注标签之间的依赖关系，并通过数据挖掘技术以概率分布函数的形式提取特征特征。我们展示了一些实验结果，即项目/标签之间的依赖关系，以查看该方法的有效性。

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Multi-label classification using labelled association

In this investigation we discuss a multi-label classification problem where documents may have several labels. We put our focus on dependencies among labels in a probabilistic manner, and we extract characteristic features in a form of probabilistic distribution functions by data mining techniques. We show some experimental results, i.e., dependencies among items/labels to see the effectiveness of the approach.

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2015 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM)

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