Knowledge extraction, research projects and archives management

Abstract

Archives play an important role in the knowledge society and must respond ever more quickly to information needs. For example, in the case of universities, research projects are a strategic asset for the growth of territories, the rationalization of financial resources and the development of archival science. Clearly, the documentation that characterizes the research projects has an administrative value as well. This paper, investigates the possibility of extracting knowledge from this class of documents. In particular, the purpose of this paper is to experiment with the application of some automatic metadata extraction tools on archival documents. An approach of metadata automatic extraction could provide a greater continuity between production and representation of objects. Metadata can be useful in accessing or sharing contents within digital preservation systems (i.e. ontologies, Linked Data). The chosen tools use Machine Learning technologies and supervised learning techniques together
with newer Deep Learning technologies.