Clustering of non-annotated data

Clustering of non-annotated data is a common problem in many areas. One of the main uses for clustering is finding structures and models in data. Because the data are unlabeled, we cannot tell if the result from clustering is the desired result. That is why we need annotated data. This can be provided from trained neural network, which works with the same or related data. (Abstract)