基于用户标签的改进K-means聚类算法

Jun Tang
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引用次数: 18

摘要

本文提出了一种基于用户标签的改进K-means聚类算法。首先利用社会标注数据对K-means的向量空间模型进行扩展。然后,利用社会标签网络中涉及的链接来提高聚类性能。实验结果表明,改进的基于用户标签的K-means聚类算法是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improved K-means Clustering Algorithm Based on User Tag
This paper proposed improved K-means clustering algorithm based on user tag. It first used social annotation data to expand the vector space model of K-means. Then, it applied the links involved in social tagging network to enhance the clustering performance. Experimental result shows that the proposed improved K-means clustering algorithm based on user tag is effective.
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