01370nas a2200121   4500008004100000245008000041210006900121260001300190520093200203100002301135700002301158856006701181       2017                        eng d00aRecognizing Residents and Tourists with Retail Data Using Shopping Profiles0 aRecognizing Residents and Tourists with Retail Data Using Shoppi  bSpringer3 aThe huge quantity of personal data stored by service providers registering customers daily life enables the analysis of individual fingerprints characterizing the customers’ behavioral profiles. We propose
a framework for recognizing residents, tourists and occasional shoppers
among the customers of a retail market chain. We employ our recognition framework on a real massive dataset containing the shopping transactions of more than one million of customers, and we identify representative temporal shopping profiles for residents, tourists and occasional
customers. Our experiments show that even though residents are about
33% of the customers they are responsible for more than 90% of the expenditure. We statistically validate the number of residents and tourists
with national official statistics enabling in this way the adoption of our
recognition framework for the development of novel services and analysis.1 aGuidotti, Riccardo1 aGabrielli, Lorenzo  uhttps://link.springer.com/chapter/10.1007/978-3-319-76111-4_35