Analyzing textual documents with new OLAP operators
Maha Azabou, Kaïs Khrouf, Jamel Feki, Chantal Soulé-Dupuy, Nathalie Vallès · 2016
As the amount of data grows very fast inside and outside of an enterprise, it is getting important to analyze both of them for getting total business intelligence. While online analytical processing (OLAP) techniques have been proven very useful for analyzing structured data, they face challenges in handling unstructured data. To this end, new multidimensional models have been proposed for OLAP purposes. Nevertheless, there is no proposal allowing managing both document structures and the semantics of the textual content. In our previous work, we proposed to integrate the entire document within a Diamond multi-dimensional model. In this paper, based on our proposed model, we provide new OLAP operators that take into account the specificities of this model.