The unsupervised neural networks are excellent tools for the analysis of high-dimensional input data as in data mining applications. In this paper different methods of data clustering are considered as the self-organizing map (SOM), neural gas (NG) and growing neural gas (GNG).This paper demonstrates, in one side, the efficiency of a viewpoint-oriented-analysis as compared to a global analysis, and in the other side, it compare these three unsupervised neural clustering methods as classifier for documentary data. For that, two quality criteria are taken into account for quality evaluation. These criteria are used as well for highlighting the clustering methods internal operation.