The use of electronic invoices helps to reduce the amount of paper used to store transaction information and offers many benefits to the companies. Indeed, it allows to speed the process, improve the efficiency, and reduce the environmental externalities. In addition, the availability of real-data on business operations ensures the timely detection of fraudulent transactions. However, the electronic invoicing process requires that all the invoices are converted to a standard electronic format, specified by local governments. In this work, we present a software tool developed to support the invoice dematerialization process in Italy. The implemented system is based on the named entity recognition model, a natural language processing technique capable of identifying the structure of the documents and automatically extrapolating the information. The developed tool has been tested by an Italian company. The results obtained are encouraging.

A Natural Language Processing Tool to Support the Electronic Invoicing Process in Italy

Di Puglia Pugliese Luigi;
2021

Abstract

The use of electronic invoices helps to reduce the amount of paper used to store transaction information and offers many benefits to the companies. Indeed, it allows to speed the process, improve the efficiency, and reduce the environmental externalities. In addition, the availability of real-data on business operations ensures the timely detection of fraudulent transactions. However, the electronic invoicing process requires that all the invoices are converted to a standard electronic format, specified by local governments. In this work, we present a software tool developed to support the invoice dematerialization process in Italy. The implemented system is based on the named entity recognition model, a natural language processing technique capable of identifying the structure of the documents and automatically extrapolating the information. The developed tool has been tested by an Italian company. The results obtained are encouraging.
2021
Istituto di Calcolo e Reti ad Alte Prestazioni - ICAR
advanced tool
e-invoicing process
named entity recognition
conditional random fields
constrained shortest path
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/463865
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 3
  • ???jsp.display-item.citation.isi??? 1
social impact