Beaver: Efficiently Building Test Collections for Novel Tasks

UDC.coleccionInvestigaciónes_ES
UDC.conferenceTitleJoint Conference of the Information Retrieval Communities in Europe (CIRCLE 2020)es_ES
UDC.departamentoCiencias da Computación e Tecnoloxías da Informaciónes_ES
UDC.endPage2es_ES
UDC.grupoInvInformation Retrieval Lab (IRlab)es_ES
UDC.issue23es_ES
UDC.startPage1es_ES
UDC.volume2621es_ES
dc.contributor.authorOtero, David
dc.contributor.authorParapar, Javier
dc.contributor.authorBarreiro, Álvaro
dc.date.accessioned2025-03-12T15:58:24Z
dc.date.available2025-03-12T15:58:24Z
dc.date.issued2020-07
dc.descriptionProceedings of the Joint Conference of the Information Retrieval Communities in Europe (CIRCLE 2020) Samatan, Gers, France, July 6-9, 2020, published at http://ceur-ws.org.es_ES
dc.description.abstract[Abstract]: Evaluation is a mandatory task for Information Retrieval research. Under the Cranfield paradigm, this evaluation needs test collections. The creation of these is a time and resource-consuming process. At the same time, new tasks and models are continuously appearing. These tasks demand the building of new test collections. Typically, the researchers organize TREC-like competitions for building these evaluation benchmarks. This is very expensive, both for the organizers and for the participants. In this paper, we present a platform to easily and cheaply build datasets for Information Retrieval evaluation without the need of organizing expensive campaigns. In particular, we propose the simulation of participant systems and the use of pooling strategies to make the most of the assessor’s work. Our platform is aimed to cover the whole process of building the test collection, from document gathering to judgment creation.es_ES
dc.description.sponsorshipThis work was supported by project RTI2018-093336-B-C22 (MCIU & ERDF), project GPC ED431B 2019/03 (Xunta de Galicia & ERDF), and accreditation ED431G 2019/01 (Xunta de Galicia & ERDF).es_ES
dc.description.sponsorshipXunta de Galicia; ED431B 2019/03es_ES
dc.description.sponsorshipXunta de Galicia; ED431G 2019/01es_ES
dc.identifier.citationOtero, D., Parapar, J., & Barreiro, Á. ‘Beaver: Efficiently Building Test Collections for Novel Tasks’, CEUR Workshop Proceedings, Vol. 2621, art. 23, pp. 1-2, 2020, Proceedings of the Joint Conference of the Information Retrieval Communities in Europe (CIRCLE 2020) Samatan, Gers, France, July 6-9, 2020.es_ES
dc.identifier.issn1613-0073
dc.identifier.urihttp://hdl.handle.net/2183/41361
dc.language.isoenges_ES
dc.publisherCEUR-WSes_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-093336-B-C22/ES/TECNOLOGIAS PARA LA PREDICCION TEMPRANA DE SIGNOS RELACIONADOS CON TRASTORNOS PSICOLOGICOS (SUBPROYECTO UDC)es_ES
dc.relation.urihttps://ceur-ws.org/Vol-2621/CIRCLE20_23.pdfes_ES
dc.rightsAtribución 4.0 Internacionales_ES
dc.rightsCopyright © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).es_ES
dc.rights.accessRightsopen accesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectInformation retrievales_ES
dc.subjectTest collectionses_ES
dc.subjectPoolinges_ES
dc.titleBeaver: Efficiently Building Test Collections for Novel Taskses_ES
dc.typeconference outputes_ES
dspace.entity.typePublication
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relation.isAuthorOfPublication.latestForDiscovery00d04042-9b75-419e-9aab-33fd14b201af

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