A Data Stream Clustering Algorithm Based Extension of Grid and Density
نویسندگان
چکیده
منابع مشابه
A Data Stream Clustering Algorithm Based Extension of Grid and Density
This study focuses on the summary data structure design and optimize the method of calculation of the mesh density and how to effectively deal with the problem of boundary points, combined with the sliding window mechanism and suggest improvements based on the mesh density of the data stream real-time clustering algorithm framework and the various parts of concrete realization of the algorithm.
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Evolving data streams are ubiquitous. Various clustering algorithms have been developed to extract useful knowledge from evolving data streams in real time. Density-based clustering method has the ability to handle outliers and discover arbitrary shape clusters whereas grid-based clustering has high speed processing time. Sliding window is a widely used model for data stream mining due to its e...
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Data mining is the method of finding the useful information in huge data repositories. Clustering is the significant task of the data mining. It is an unsupervised learning task. Similar data items are grouped together to form clusters. These days the clustering plays a major role in every day-to-day application. In this paper, the field of KDD i.e. Knowledge Discovery in Databases, Data mining...
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ژورنال
عنوان ژورنال: Research Journal of Applied Sciences, Engineering and Technology
سال: 2013
ISSN: 2040-7459,2040-7467
DOI: 10.19026/rjaset.6.4067