2.2. Benefit two: reducing noises of data

Even when the information contained in single-view data is complete, there may exist some unavoidable noises. It is apparent that data cleaning is one critical issue in data analysis, which can tremendously affect the performance of clustering algorithms. It is quite hard and costly to remove all the noises of data, and thus single-view noisy data usually leads to unsatisfactory clustering results. On the other hand, multi-view clustering is able to circumvent the side effect of noises or corrupted data in each view and emphasize the common patterns shared by multiview data.
