Articles by Laura Cignoni

The advances of digital technology to the museum world have led to the development of computational tools for the classification of information as well as consultation of semantically correlated documents. The work presented here consists in an experiment, organizing the textual descriptions relative to iconographic works by means of SOM (Self-Organizing Maps), which represent the most common algorithm of artificial neural networks in the category of non-supervised learning, i.e. without the control and contribution of knowledge on the part of the human operator. The system produces a bi-dimensional map in which the words, represented graphically by means of semantically correlated nodes, are contiguous and form agglomerates. Therefore, the visit to a virtual museum containing works located in different sites can take place following pathways which are “conceptually-oriented”, independent of the learner’s cultural background.