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Fuzzy clustering for TV program classification

机译:电视节目分类的模糊聚类

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摘要

In order to achieve TV program group recommendation, an approach based on fuzzy clustering is proposed for program classification. We first describe the XML based program description metadata representation, in which both textual and symbolic information is included. Secondly it presents the program feature extraction and presentation method. A program is defined as two vectors, one is based on term statistics implying what the program is about, and the other reflects broadcasting characteristics of the program. Then the classifying approach based on fuzzy clustering is proposed. The approach goes: normalizing original data, building fuzzy similarity matrix, and then clustering. The final fuzzy similarity matrix is constructed by combining two fuzzy similarity matrices calculated from two different aspects.
机译:为了实现电视节目群推荐,提出了一种基于模糊聚类的节目分类方法。我们首先描述基于XML的程序描述元数据表示,其中包含文本和符号信息。其次介绍了程序特征的提取与表示方法。一个节目被定义为两个向量,一个向量是基于暗示该节目内容的术语统计信息,另一个则反映了该节目的广播特性。然后提出了一种基于模糊聚类的分类方法。方法是:对原始数据进行标准化,建立模糊相似矩阵,然后进行聚类。通过组合从两个不同方面计算出的两个模糊相似度矩阵,构造最终的模糊相似度矩阵。

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