Topic Identification in Soft Clustering using PCA and ICA
نویسندگان
چکیده
Many applications can benefit from soft clustering, where each datum is assigned to multiple clusters with membership weights that sum to one. In this paper we present a comparison of principal component analysis (PCA) and independent component analysis (ICA) when used for soft clustering. We provide a short mathematical background for these methods and demonstrate their application to a sponsored links search listings dataset. We present examples of the soft clusters generated by both methods and compare the results.
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تاریخ انتشار 2004