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Part 1 INTRODUCTION.
The goal of clustering is to divide a set of objects into a finite and discrete set of clusters, in which objects in the same cluster are similar, while objects in different cluster are dissimilar follow some criteria of user domain.
Though clustering algorithms have long history, nowadays clustering topic has still attracted a lot of attentions, because of the need of efficient data analysis tools in many applications, such as web mining, spatial database analysis, GIS, textual document collection, image segmentation, etc.
Given a data set of objects, clustering can detect the relation between data objects and the hidden structure of whole data objects and hence, it is the important tool in the data mining and knowledge discovery process. |
IEEE/ICACT20220068 Slide.03
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