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- W323352447 abstract "Data clustering is a data analysis technique that groups data based on a measure of similarity. When data is well clustered the similarities between the objects in the same group are high, while the similarities between objects in different groups are low. The data clustering technique is widely applied in a variety of areas such as bioinformatics, image segmentation and market research. This project conducted an in-depth study on data clustering with focus on density-based clustering methods. The latest density-based (CFSFDP) algorithm is based on the idea that cluster centers are characterized by a higher density than their neighbours and by a relatively larger distance from points with higher densities. This method has been examined, experimented, and improved. These methods (KNN-based, Gaussian Kernelbased and Iterative Gaussian Kernel-based) are applied in this project to improve (CFSFDP) density-based clustering. The methods are applied to four milestone datasets and the results are analyzed and compared." @default.
- W323352447 created "2016-06-24" @default.
- W323352447 creator A5020123382 @default.
- W323352447 date "2015-01-01" @default.
- W323352447 modified "2023-09-26" @default.
- W323352447 title "Density Based Data Clustering" @default.
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