ArticleAuthors: Lê, Thị Cẩm Bình; Phạm, Văn Nha; Phạm, Thế Long (2021)
The development of information and com- munication technology has motivated multi- source data to become more common and publicly available. Compared to traditional data that describe objects from a single- source, multi-source data is semantically richer, more useful, however many-feature, more uncertain, and complex. Since tra- ditional clustering algorithms cannot han- dle such data, multi-source clustering has become a research hotspot. Most existing multi-source clustering methods are devel- oped from single-source clustering by ex- tending the objective function or building combination models. In fact, the fuzzy clus- tering methods handle the uncertainty data better than the hard clustering methods. Re- cently, fuzzy co-clustering has proven effec- tive in the many-feature da... 
