Unsupervised multi-view learning is a hot research topic. The main challenge lies in how to integrate information from different views to enhance the unsupervised learning performance. In this paper, we present our research works on multi-view data clustering and multi-view network community detection respectively. The main contributions are summarized by emphasizing the challenges we have addressed. In addition, the ongoing work and the future work are briefly presented.