Graphical representation of statistics hidden in unstructured data: A software application
Maha Mallek, Ramzi Guetari, Nejmeddine Etteyeb, Walid Ghariani · 2017
The unstructured data, which volume grows exponentially, often hide important and even vital information for society and companies. It takes a lot of work to extract information such as the nature of consumption in a category of individuals, trends, etc. When it comes to statistical data, it is often very useful to synthesize this kind of information in the form of graphical representations. In this paper, we present an approach for processing unstructured data containing statistics in order to represent them graphically. An application that implements this process is also presented.