Data stream clustering is defined as the clustering of data that arrive continuously such as telephone records, multimedia data, financial transactions etc.
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The data stream model is relevant to new classes of applications involving massive data sets, such as web click stream analysis and multimedia data analysis. We ...
We study clustering under the data stream model of computation where: given a sequence of points, the objective is to maintain a consistently good clustering.
Jul 16, 2020 · Clustering is one of the most suitable methods for real-time data stream processing, because it can be applied with less prior information about ...
Jul 13, 2020 · Data stream clustering refers to the clustering of data that arrives continually such as financial transactions, multimedia data, ...
Data Stream Clustering (DSC) plays an important role in mining continuous and unlabeled data streams in real-world applications. Over the last decades, ...
Dec 1, 2016 · This paper presents a comprehensive survey of the data stream clustering methods and an overview of the most well-known streaming platforms which implement ...
Jan 14, 2003 · For analysis of such data, the ability to process the data in a single pass, or a small number of passes, while using little memory, is crucial.
The clustering problem is a difficult problem for the data stream domain. This is because the large volumes of data arriving in a stream.
Jun 20, 2023 · Data Stream Clustering (DSC) plays an important role in mining continuous and unlabeled data streams in real-world applications.
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