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

Author:

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

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.

Publisher

Emerald

Subject

Public Administration

Reference34 articles.

1. Innovative services to ease the access to the public,2011

2. Towards a pan-european E-procurement platform to aggregate, publish and search public procurement notices powered by linked open data: the moldeas approach;International Journal of Software Engineering and Knowledge Engineering,2012

3. An adaptation of the vector-space model for ontology-based information retrieval;IEEE Transactions on Knowledge and Data Engineering,2007

4. LOTED2: an ontology of European public procurement notices;Semantic Web,2016

5. Building an automatic e-tendering system on the semantic web;Decision Support Systems,2009

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3