A Survey on Unsupervised Transfer Clustering

Feng Wang, Lianmeng Jiao, Quan Pan

科研成果: 书/报告/会议事项章节会议稿件同行评审

5 引用 (Scopus)

摘要

Clustering is widely used in analysis, natural language processing, image segmentation and other data mining fields. However, traditional clustering algorithms, such as K-means, can produce good clustering result only when the instance size is large enough. When the instance size is insufficient, the clustering result will be poor. One way to solve this problem is transfer learning. At present, researches on transfer learning mainly focus on classification and recognition, while researches on clustering are very limited, but become more and more promising. This survey focuses on categorizing and reviewing the current progress on unsupervised transfer clustering algorithm. We also explore some potential future issues in unsupervised transfer clustering research.

源语言英语
主期刊名Proceedings of the 40th Chinese Control Conference, CCC 2021
编辑Chen Peng, Jian Sun
出版商IEEE Computer Society
7361-7365
页数5
ISBN(电子版)9789881563804
DOI
出版状态已出版 - 26 7月 2021
活动40th Chinese Control Conference, CCC 2021 - Shanghai, 中国
期限: 26 7月 202128 7月 2021

出版系列

姓名Chinese Control Conference, CCC
2021-July
ISSN(印刷版)1934-1768
ISSN(电子版)2161-2927

会议

会议40th Chinese Control Conference, CCC 2021
国家/地区中国
Shanghai
时期26/07/2128/07/21

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