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首页> 外文期刊>International Journal of Applied Engineering Research >Clustering by Enhancing Co-occurrence Frequency
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Clustering by Enhancing Co-occurrence Frequency

机译:通过增强共出频率来聚类

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摘要

Despite that the methodologies for document clustering are abundant in the research literature, the need for it still persists. Due to the large dimensionality and huge amount of resources to be searched, there is tremendous need for algorithms to be developed to mine the knowledge. In this research, the documents are represented using the term frequency, and it is converted into a vector by augmenting some of the features using frequent sets. Bisecting k-means algorithm is used to cluster the data. By changing the bounds on the similarity measures, various clusters can be obtained.
机译:尽管文档聚类方法在研究文献中丰富了,但需要它仍然存在。 由于较大的维度和巨大的资源进行了搜索,巨大地需要开发算法来挖掘知识。 在本研究中,使用术语频率表示文档,通过使用频繁的集合增强一些特征,将其转换为向量。 B分配K-Means算法用于聚类数据。 通过改变相似度测量的界限,可以获得各种簇。

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