By learning the features of each view, the potential patterns and structures of the data are discovered and fused to improve the accuracy and stability of data stream clustering for better ...

Currently, multi-view representation learning algorithms have been widely used and their prospects are very promising. For example, in the financial field, it can be used for customer segmentation ...

The multi-view representation learning algorithm can effectively deal with the data stream clustering problem by jointly learning multiple-view representations and combining them with traditional ...

The multi-view representation learning algorithm can better handle noise and outliers in the data, making the clustering results more reliable. The multi-view representation learning algorithm can ...