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

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.