Innovative Approaches of Historical Newspapers: Data Mining, Data Visualization, Semantic Enrichment

Abstract

In this age of Big Data this paper describes how digital librairies can apply at large scale innovative approaches to better valorize and bring better experiences of old newspapers. On the first hand, the state-of-the-art OLR (optical layout recognition) technique in one of the largest heritage press digitization projects in Europe (Europeana Newspapers, www.europeana-newspapers.eu, 2012-2015) was used in a data mining experiment. Data analysis was applied to quantitative metadata derived from a 850K pages subset of six XIXth-XXth c. French newspaper titles from the BnF collection. The METS/ALTO XML data was analyzed with data mining and data visualization techniques that show promising ways for the production of knowledge about historical newspapers that are of great interest for library professionals (digitization programs management, curation and mediation of newspaper collections) and for end-users, particularly the digital humanities community. On the other hand, the Retronews web portal showcases how advanced semantic annotation techniques can improve the retrieval efficiency on a digital newspapers collection; thus the rediscovery and reappropriation of these documents by various types of users: teachers, students, researchers, general public.