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Seminar: Density-Based Clustering and Its Application

November 21, 2013 @ 2 p.m.

Fang Liu (Associate Professor, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China)


Clustering is the problem of finding a set of groups of similar objects within a data set while keeping dissimilar objects separated in different groups or the group of noise. It is a common technique for statistical data analysis, and used in many fields, including machine learning, pattern recognition, data mining, image analysis, information retrieval, and bioinformatics. Density based clustering techniques are attractive because it can find arbitrary shaped clusters along with noisy outliers. In this talk, the density based clustering methods will be discussed, and the result of applying them in different area (such as text extraction from image, postmortem estimation from eye image) is presented as well.