Mostrar o rexistro simple do ítem

dc.contributor.authorLosada, David E.
dc.contributor.authorCrestani, Fabio
dc.contributor.authorParapar, Javier
dc.date.accessioned2020-05-18T13:43:22Z
dc.date.available2020-05-18T13:43:22Z
dc.date.issued2020-04-08
dc.identifier.citationLosada D.E., Crestani F., Parapar J. (2020) eRisk 2020: Self-harm and Depression Challenges. In: Jose J. et al. (eds) Advances in Information Retrieval. ECIR 2020. Lecture Notes in Computer Science, vol 12036. Springer, Cham. https://doi.org/10.1007/978-3-030-45442-5_72es_ES
dc.identifier.isbn9783030454418
dc.identifier.isbn9783030454425
dc.identifier.issn0302-9743
dc.identifier.urihttp://hdl.handle.net/2183/25590
dc.description.abstract[Abstract] This paper describes eRisk, the CLEF lab on early risk prediction on the Internet. eRisk started in 2017 as an attempt to set the experimental foundations of early risk detection. Over the last three editions of eRisk (2017, 2018 and 2019), the lab organized a number of early risk detection challenges oriented to the problems of detecting depression, anorexia and self-harm. We review in this paper the main lessons learned from the past and we discuss our future plans for the 2020 edition.es_ES
dc.description.sponsorshipWe thank the support obtained from the Swiss National Science Foundation (SNSF) under the project “Early risk prediction on the Internet: an evaluation corpus”, 2015. We also thank the financial support obtained from the (i) “Ministerio de Ciencia, Innovación y Universidades” of the Government of Spain (research grants RTI2018-093336-B-C21 and RTI2018-093336-B-C22), (ii) “Consellería de Educación, Universidade e Formación Profesional”, Xunta de Galicia (grants ED431C 2018/29, ED431G/08 and ED431G/01 – “Centro singular de investigación de Galicia” –). All grants were co-funded by the European Regional Development Fund (ERDF/FEDER program)es_ES
dc.description.sponsorshipXunta de Galicia; ED431C 2018/29es_ES
dc.description.sponsorshipXunta de Galicia; ED431G/08es_ES
dc.description.sponsorshipXunta de Galicia; ED431G/01es_ES
dc.language.isoenges_ES
dc.publisherSpringeres_ES
dc.relationinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-093336-B-C21/ES/TECNOLOGIAS PARA LA PREDICCION TEMPRANA DE SIGNOS RELACIONADOS CON TRASTORNOS PSICOLOGICOS
dc.relationinfo: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)
dc.relation.urihttps://doi.org/10.1007/978-3-030-45442-5_72es_ES
dc.rights© Springer Nature Switzerland AG 2020
dc.subjecteRiskes_ES
dc.subjectDepressiones_ES
dc.subjectAnorexiaes_ES
dc.subjectSelf-harmes_ES
dc.titleeRisk 2020: autolesiones y desafíos de la depresiónes_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES
UDC.journalTitleLecture Notes in Computer Sciencees_ES
UDC.volume12036es_ES
dc.identifier.doi10.1007/978-3-030-45442-5_72
UDC.conferenceTitle42ª Conferencia Europea sobre Investigación IR, ECIR 2020, Lisboa, Portugal, 14-17 de abril de 2020es_ES


Ficheiros no ítem

Thumbnail

Este ítem aparece na(s) seguinte(s) colección(s)

Mostrar o rexistro simple do ítem