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Recently, semi-supervised clustering has received a lot of attentions in researcher communities . The advantage of semi-supervised clustering consists in possibility to use a small set of side information to improve clustering results. Constraints include must-link and cannot-link. In real applications, we hypothesis that the side information is available or can be collected from users/experts. For example, in our research in 2020, A Density-based Approach for Querying Informative Constraints for Clustering, we studied that the general idea has been rising when we work with the semi-supervised clustering problem. The above figure shows a schema for semi-supervised clustering. |
IEEE/ICACT20220071 Slide.04
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