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This study aims at exploring both the identity of the maenads and their multiple interactions with the satyrs on Athenian red-figure vases by presenting the preliminary results of an ANN-based analysis applied to a dataset of 114 vases representing 478 figures (maenads and satyrs). The encouraging results seem to confirm the highly significant role of ANN-based methodologies as innovative tools for the organisation, visualisation and analysis of complex data in History of Art and Archaeology. Further explorations of these methodologies, associated with higher levels of data formalisation, should open new perspectives for the research on Athenian iconography and iconology.

In this paper the theoretical and methodological aspects of some of the tools applied to the archaeological, geographical and linguistic problems posed by ARCHEOSEMA project will be analysed. In particular, the single steps of the process of generation of outputs, from the initial analysis of the dataset, the subsequent procedures of pre-processing and encoding of the data to the characteristics of the processing algorithms will be described. For this purpose we will use a so-called toy dataset known in the literature. Using the same dataset, we will illustrate the main output produced, Minimum Spanning Tree maps. Along with the use of classical literature measurements, such as the Pearson linear correlation and Prior Probability, both used as metrics for the generation of these outputs, we have tried to show the innovative contribution of a new artificial neural network, the Auto-Contractive Map, designed by P.M. Buscema at the Semeion Research Center.