Public procurement is viewed as a major market force that can be used to promote innovation and drive small and medium-sized enterprises growth. In such cases, procurement system design relies on intermediates that provide vertical linkages between suppliers and providers of innovative services and products. In this work we propose an innovative methodology for decision support in the process of supplier discovery, which precedes the final supplier selection. We focus on data gathered from community-based sources such as Reddit and Wikidata and avoid any use of historical open procurement datasets to identify small and medium sized suppliers of innovative products and services that own very little market shares. We look into a real-world procurement case study from the financial sector focusing on the Financial and Market Data offering and develop an interactive web-based support tool to address certain requirements of the Italian central bank. We demonstrate how a suitable selection of natural language processing models, such as a part-of-speech tagger and a word-embedding model, in combination with a novel named-entity-disambiguation algorithm, can efficiently analyze huge quantity of textual data, increasing the probability of a full coverage of the market.

Automated Natural Language Processing-Based Supplier Discovery for Financial Services / Papa, Mauro; Chatzigiannakis, Ioannis; Anagnostopoulos, Aristidis. - In: BIG DATA. - ISSN 2167-6461. - (2023), pp. 1-19. [10.1089/big.2022.0215]

Automated Natural Language Processing-Based Supplier Discovery for Financial Services

Ioannis Chatzigiannakis
Co-primo
Conceptualization
;
Aris Anagnostopoulos
Ultimo
Methodology
2023

Abstract

Public procurement is viewed as a major market force that can be used to promote innovation and drive small and medium-sized enterprises growth. In such cases, procurement system design relies on intermediates that provide vertical linkages between suppliers and providers of innovative services and products. In this work we propose an innovative methodology for decision support in the process of supplier discovery, which precedes the final supplier selection. We focus on data gathered from community-based sources such as Reddit and Wikidata and avoid any use of historical open procurement datasets to identify small and medium sized suppliers of innovative products and services that own very little market shares. We look into a real-world procurement case study from the financial sector focusing on the Financial and Market Data offering and develop an interactive web-based support tool to address certain requirements of the Italian central bank. We demonstrate how a suitable selection of natural language processing models, such as a part-of-speech tagger and a word-embedding model, in combination with a novel named-entity-disambiguation algorithm, can efficiently analyze huge quantity of textual data, increasing the probability of a full coverage of the market.
2023
supplier discovery; financial services; entity linking; natural language processing; named-entity disambiguation
01 Pubblicazione su rivista::01a Articolo in rivista
Automated Natural Language Processing-Based Supplier Discovery for Financial Services / Papa, Mauro; Chatzigiannakis, Ioannis; Anagnostopoulos, Aristidis. - In: BIG DATA. - ISSN 2167-6461. - (2023), pp. 1-19. [10.1089/big.2022.0215]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1685966
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