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- W4386700900 abstract "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 summarizer, an open information extraction engine in the form of triples (subject–predicate–object) for tender documents, and dashboards for analysing tender data." @default.
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- W4386700900 date "2023-10-01" @default.
- W4386700900 modified "2023-09-28" @default.
- W4386700900 title "AI-based decision support system for public procurement" @default.
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- W4386700900 doi "https://doi.org/10.1016/j.is.2023.102284" @default.
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