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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 in this paper. This paper firstly describes 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:为了实现电视节目组建议,提出了一种基于模糊聚类的方法,以便在本文中进行计划分类。本文首先描述了基于XML的程序描述元数据表示,其中包括文本和符号信息。其次,它提出了程序特征提取和呈现方法。程序被定义为两个向量,一个是基于术语统计信息,这意味着该程序的约定,另一个反映了程序的广播特征。然后提出了基于模糊群集的分类方法。该方法是:归一化原始数据,构建模糊相似度矩阵,然后群集。通过组合由两个不同方面计算的两个模糊相似性矩阵来构造最终的模糊相似性矩阵。

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