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A partitioning based algorithm to fuzzy co-cluster documents and words

机译:一种基于分割的模糊共聚文档和单词算法

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摘要

In this paper, a new algorithm fuzzy co-clustering with Ruspini's condition (FCR) is proposed for co-clustering documents and words. Compared to most existing fuzzy co-clustering algorithms, FCR is able to generate fuzzy word clusters that capture the natural distribution of words, which may be beneficial for information retrieval. We discuss the principle behind the algorithm through some theoretical discussions and illustrations. These, together with experiments on two standard datasets show that FCR can discover the naturally existing document-word co-clusters.
机译:本文提出了一种基于鲁斯皮尼条件的模糊联合聚类算法,用于文档和单词的联合聚类。与大多数现有的模糊共聚算法相比,FCR能够生成捕获单词自然分布的模糊单词簇,这可能对信息检索有利。我们将通过一些理论上的讨论和说明来讨论算法背后的原理。这些以及在两个标准数据集上的实验表明,FCR可以发现自然存在的文档单词共簇。

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