CIODD : Cluster Identification and Outlier Detection in Distributed Data

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Provided by: Oriental Scientific
Topic: Big Data
Format: PDF
Clustering has become an increasingly important task in modern application domains such as marketing and purchasing assistance, multimedia, molecular biology etc. The goal of clustering is to decompose or partition a data set into groups such that both the intra-group similarity and the intergroup dissimilarity are maximized. In many applications, the size of the data that needs to be clustered is much more than what can be processed at a single site. Further, the data to be clustered could be inherently distributed.
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