Matchmaking Public Procurement Linked Open Data
An increasing amount of public procurement data is nowadays being ported to linked data format, in view of its exploitation by government, commercial as well as non-profit subjects. One of the crucial tasks in public procurement is matchmaking demand with supply. We conceived this task as that of fi...
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Published in | On the Move to Meaningful Internet Systems: OTM 2015 Conferences Vol. 9415; pp. 405 - 422 |
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Main Authors | , , |
Format | Book Chapter |
Language | English |
Published |
Switzerland
Springer International Publishing AG
2015
Springer International Publishing |
Series | Lecture Notes in Computer Science |
Subjects | |
Online Access | Get full text |
ISBN | 9783319261478 3319261479 |
ISSN | 0302-9743 1611-3349 |
DOI | 10.1007/978-3-319-26148-5_27 |
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Abstract | An increasing amount of public procurement data is nowadays being ported to linked data format, in view of its exploitation by government, commercial as well as non-profit subjects. One of the crucial tasks in public procurement is matchmaking demand with supply. We conceived this task as that of finding a supplier with previous successful history of contracts similar to a current call for tenders. In this paper we show how to implement a portable matchmaking service that relies solely on the capability of SPARQL 1.1. In order to show its effectiveness, the proposed service has been tested and evaluated on the RDFized versions of 2 procurement databases: the European Union’s Tenders Electronic Daily and the Czech public procurement register. We evaluate several factors influencing matchmaking accuracy, including score aggregation and weighting, query expansion, contribution of additional features obtained from linked data, data quality and volume. |
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AbstractList | An increasing amount of public procurement data is nowadays being ported to linked data format, in view of its exploitation by government, commercial as well as non-profit subjects. One of the crucial tasks in public procurement is matchmaking demand with supply. We conceived this task as that of finding a supplier with previous successful history of contracts similar to a current call for tenders. In this paper we show how to implement a portable matchmaking service that relies solely on the capability of SPARQL 1.1. In order to show its effectiveness, the proposed service has been tested and evaluated on the RDFized versions of 2 procurement databases: the European Union’s Tenders Electronic Daily and the Czech public procurement register. We evaluate several factors influencing matchmaking accuracy, including score aggregation and weighting, query expansion, contribution of additional features obtained from linked data, data quality and volume. |
Author | Svátek, Vojtěch Di Noia, Tommaso Mynarz, Jindřich |
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Copyright | Springer International Publishing Switzerland 2015 |
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Editor | Weichhart, Georg Dillon, Tharam Ardagna, Claudio Agostino Debruyne, Christophe An, Yuan Meersman, Robert Panetto, Hervé |
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SubjectTerms | Artificial intelligence Information retrieval Linked open data Matchmaking Public procurement Software Engineering SPARQL |
Title | Matchmaking Public Procurement Linked Open Data |
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