Graphical document representation for french newsletters analysis
Résumé
Document analysis is essential in many industrial applications. However, engineering natural language resources to represent entire documents is still challenging. Besides, available resources in French are scarce and do not cover all possible tasks, especially in specific business applications. In this context, we present a French newsletter dataset and its use to predict the good or bad impact of newsletters on readers. We propose a new representation of newsletters in the form of graphs that consider the newsletters' layout. We evaluate the relevance of the proposed representation to predict a newsletter's performance in terms of open and click rates using graph analysis methods.