Automatic Induction of Rules for Classification and Interpretation of Cultural Heritage Material

This work presents the application of incremental symbolic learning strategies for the automatic induction of classification and interpretation rules in the cultural heritage domain. Specifically, such experience was carried out in the environment of the EU project COLLATE, in whose architecture the incremental learning system INTHELEX is used as a learning component. Results are reported, proving that the system was able to learn highly reliable rules for such a complex task.