Though these approaches have had some success, learning algorithms are achieving higher accuracy recently with big data and powerful computers. With few assumptions and little manual interference, structures similar to the hierarchical cone are being automatically learned from large amounts of data. These learning approaches are especially interesting in that, because they learn, they are not fixed for any specific task, and they can be used in a variety of applications.
