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Graph Based Clustering With Constraints And Active Learning / Vu Tuan Dang, Vu Viet Vu, Do Hong Quan // Tạp chí Tin học và Điều khiển học = Journal of Computer Science And Cybernetics . - 2021. - tr. 73-91. - ISSN: 1813-9663
Ký hiệu phân loại (DDC): 006.3
During the past few years, semi-supervised clustering has emerged as adirection in machine learning research. In a semi-supervised clustering algorithm. tie frying results can be significantly improved by using side information, which is available or Grille; e-d from users. There are two main kinds of side information that can be learned in semi-superfse- lose-ring algorithms including class labels(seeds) or pairwise constraints. In this paper. we trig supervised graph based clustering algorithm that tries to use seeds and constraints 1 .process, called MCSSGC. Moreover, we also introduce a simple but efficient active {-eamethod to collect the constraints that can boost the performance of MCSSGC, named. Three obtained results Show that the proposed algorithm can significantly improve the compared to some recent algorithms.
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