PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Pennacchioli D., Coscia M., Giannotti F., Pedreschi D. Calculating Product and Customer Sophistication on a Large Transactional Dataset. Technical report, 2013.
 
 
Abstract
(English)
The market basket transactions observed at microscale (each individual product bought by each individual customer at each store visit) over a large population for a long time, offer a detailed picture of customers' shopping activity. Given the high cardinality of such a detailed dataset, data mining techniques have been developed to let the hidden knowledge emerge from it. In this technical report, we propose to use the system of all customer-product connections as a whole. We create a framework able to exploit the characteristics of the customer-product matrix and we test it on a unique transaction database, recording the micro-purchases of a million customers observed for several years at the stores of the top national supermarket retailer. We propose it as a novel analytic paradigm for market basket analysis, a paradigm that is challenging both conceptually, given the high complexity of the structures we build, and computationally, given the scale of the data it needs to analyze
Subject Customer Behavior
Data Mining
Economic Complexity
H.2.8 Database applications. Data mining
J.4 Computer Applications. Social and Behavioral Science. Economics


Icona documento 1) Download Document PDF


Icona documento Open access Icona documento Restricted Icona documento Private

 


Per ulteriori informazioni, contattare: Librarian http://puma.isti.cnr.it

Valid HTML 4.0 Transitional