文章基本信息

标题：An Efficient Hubness Clustering Model For High Dimensional Data
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作者：V.Geetha ; G.Bharathi
期刊名称：International Journal of Computer Trends and Technology
电子版ISSN：2231-2803
出版年度：2015
卷号：30
期号：2
页码：81-86
出版社：Seventh Sense Research Group
摘要：High dimensional data clustering can be seen in all fields these days and is becoming very tedious process. The important disadvantage of high dimensional data which we can give is that of the curse of dimensionality. As the magnitude of data sets grows the data points become sparse and density of the area becomes less making it difficult to cluster that data which further reduces the performance of traditional algorithms used for clustering .The organization maintains customer or product information in different forms which is difficult to perform clustering. Each data point has different in size and properties, but has to be clustered in meaningful and efficient way to get some knowledge from that. Many strategies have been proposed for clustering high dimensional data, but suffer with the problem of overlapping and retrieval efficiency. The proposed algorithm is basically used for increasing efficiency and accuracy.
关键词：Dataclustering; Sparsity; Hubness; Nearest neighbours.