The COLLATE project is concerned with digitised historical material. One of the main features of COLLATE system architecture is the integration of software components that exploit state-of-the-art techniques coming from the area of Artificial Intelligence and Knowledge Representation (KR). This work describes the results achieved by applying Machine Learning methods for automatic classification and labelling of documents. Furthermore, we also discuss the advantages obtained by exploiting brand new research achievements in KR for the design of COLLATE data model.
Automatic Management of Annotations on Cultural Heritage Material
SEMERARO, Giovanni;ESPOSITO, Floriana;FERILLI, Stefano;BASILE, TERESA MARIA;DI MAURO, NICOLA;
2004-01-01
Abstract
The COLLATE project is concerned with digitised historical material. One of the main features of COLLATE system architecture is the integration of software components that exploit state-of-the-art techniques coming from the area of Artificial Intelligence and Knowledge Representation (KR). This work describes the results achieved by applying Machine Learning methods for automatic classification and labelling of documents. Furthermore, we also discuss the advantages obtained by exploiting brand new research achievements in KR for the design of COLLATE data model.File in questo prodotto:
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