ArticleAuthors: Lê, Thị Cẩm Bình; Phạm, Văn Nha; Ngô, Thành Long (2021)
In modern data analysis, multi-source data appears more and more in real applications. Different data sources provide information about different data. Therefore, multi-source data linking is important to improve the processing performance. However, in practice multi-source data is often heterogeneous, un- certain, and large. This issue is considered a major challenge from multi-source data. Ensemble is a universal machine learning model in which learning techniques can work in parallel, with big data. Clustering ensemble has been shown to outperform any standard clustering algorithm in terms of ac- curacy and robustness. However, most of the traditional clustering ensemble approaches are based on single-objective function and single-source dataIn this paper, we pro- pose a new clus... 
