Application of a semantic product matching mechanism in open tendering e-marketplaces

Ahmad Mehrbod, Aneesh Zutshi, António Grilo and Ricardo Jardim-Gonsalves

Journal of Public Procurement, 2018, vol. 18, issue 1, 14-30

Abstract: Purpose - Searching the tender notices that publish every day in open tendering websites is a common way for finding business opportunity in public procurement. The heterogeneity of tender notices from various tendering marketplaces is a challenge for exploiting semantic technologies in the tender search. Design/methodology/approach - Most of the semantic matching approaches require the data to be structured and integrated according to a data model. But the integration process can be expensive and time-consuming especially for multi-source data integration. Findings - In this paper, a product search mechanism that had been developed in an e-procurement platform for matching product e-catalogues is applied to the tender search problem. The search performance has been compared using two procurement vocabularies on searching tender notices from two major tender resources. Originality/value - The test results show that the matching mechanism is able to find tender notices from heterogeneous resources and different classification systems without transforming the tenders to a uniform data model.

Keywords: Public procurement; Tender notice; Semantic matching; Classification systems (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:eme:jopppp:jopp-03-2018-002

DOI: 10.1108/JOPP-03-2018-002

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