提出了一种基于概念层次树的主题词轮排选择的实现算法。
Based on human imitation, a concept hierarch tree based rotational model is developed to choose the final subject words.
其中概念层次树作为一种统计类的数据分类方法在面向属性的归纳分类方法中起着重要作用。
Conception Hierarchy Tree classifiers which is a statistical approach have played an important role in Attribute-Oriented Induction.
提出一种视频的分层语义联想模型，构造三个层次的信息：概念层次树，场景网络和语义对象网络。
A hierarchical semantic associative video model was proposed which described video information in hierarchical concept tree, scene network and semantic object net.
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