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Information processing apparatus, method, and program for obtaining weight for each feature amount in subjective hierarchical clustering

机译:用于在主观层次聚类中获得每个特征量的权重的信息处理设备,方法和程序

摘要

To learn the weight of each physical feature so that hierarchical clustering reflecting the degree of subjective similarity can be performed. An information processing apparatus of the present invention acquires multiple pieces of content separated in a set of three pieces (hereinafter referred to as a triplet) together with label information as training data, the label information indicating a pair specified by a user as having the highest degree of similarity among three contents of the triplet. The information processing apparatus executes hierarchical clustering using a feature vector of each piece of content of the training data and the weight of each feature to determine the hierarchical structure of the training data. The information processing apparatus updates the weight of each feature so that the degree of agreement between a pair combined first as being the same clusters among three contents of the triplet in a determined hierarchical structure and a pair indicated by label information corresponding to the triplet increases.
机译:要了解每个物理特征的权重,以便可以执行反映主观相似度的层次聚类。本发明的信息处理设备获取以三部分(以下称为三元组)为一组的多个内容以及标签信息作为训练数据,标签信息指示用户指定的一对具有最高的信息。三元组的三个内容之间的相似程度。信息处理设备使用训练数据的每个内容的特征向量和每个特征的权重来执行分层聚类,以确定训练数据的分层结构。信息处理设备更新每个特征的权重,以使得在确定的分层结构中首先组合为三元组的三个内容中的相同簇的一对与由对应于三元组的标签信息表示的对之间的一致程度增加。

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