AI-based decision support system for public procurement

• Published in: Information systems (Oxford) Vol. 119; p. 102284
• Main Authors: Siciliani, Lucia, Taccardi, Vincenzo, Basile, Pierpaolo, Di Ciano, Marco, Lops, Pasquale
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.10.2023
• Subjects: Data analysis; Data visualisation; Decision support systems; E-procurement; Natural language processing; Semantic search; Decision support systems; E-procurement; Data analysis; Natural language processing; Data visualisation; Semantic search
• ISSN: 0306-4379; 1873-6076
• DOI: 10.1016/j.is.2023.102284

Tenders are powerful means of investment of public funds and represent a strategic development resource. Thus, improving the efficiency of procuring entities and developing evaluation models turn out to be essential to facilitate e-procurement procedures. With this contribution, we introduce our research to create a supporting system for the decision-making and monitoring process during the entire course of investments and contracts. This system employs artificial intelligence techniques based on natural language processing, focused on providing instruments for extracting useful information from both structured and unstructured (i.e., text) data. Therefore, we developed a framework based on a web app that provides integrated tools such as a semantic search engine, a summariser, an open information extraction engine in the form of triples (subject–predicate–object) for tender documents, and dashboards for analysing tender data. •A Decision Support System integrating structured/unstructured data about tenders.•Semantic search engine for tenders documentation to allow information retrieval.•Search engine based on OIE (Open Information Extraction) techniques.•Use of Business Intelligence tools to visualise and analyse procurement data.•Integration of collusion risk indicators allows users to detect anomalies.