Public tenders, complaints, machine learning and recommender systems: a case study in public administration.

With the proliferation of e-procurement systems in the public sector, valuable and open information sources can be jointly accessed. Our research aims to explore different legal Open Data; in particular, we explored the data set of the National Anti-Corruption Authority in Italy on public procurement and the judges' sentences related to public procurement, published on the website of the Italian Administrative Justice from 2007 to 2022. Our first goal was to train machine learning models capable of automatically recognizing which procurement has led to disputes and consequently complaints to the Administrative Justice, identifying the relevant features of procurement that correspond to certain anomalies. Our second goal was to develop a recommender system on procurement to return similar procurement to a given one and find companies for bidders, depending on the procurement requirements. [ABSTRACT FROM AUTHOR]