Utilize este identificador para referenciar este registo:
http://hdl.handle.net/10071/22565
Registo completo
Campo DC | Valor | Idioma |
---|---|---|
dc.contributor.author | Messejana, J. | - |
dc.contributor.author | Pereira, R. | - |
dc.contributor.author | Ferreira, J. C. | - |
dc.contributor.author | Baptista, M. | - |
dc.contributor.editor | S. I. Ao and Len Gelman and David WL Hukins and Andrew Hunter and A. M. Korsunsky | - |
dc.date.accessioned | 2021-05-12T10:07:25Z | - |
dc.date.available | 2021-05-12T10:07:25Z | - |
dc.date.issued | 2019 | - |
dc.identifier.isbn | 978-988-14048-6-2 | - |
dc.identifier.issn | 2078-0958 | - |
dc.identifier.uri | http://hdl.handle.net/10071/22565 | - |
dc.description.abstract | A high number of IT organizations have problems when deploying their services, this alongside with the high number of services that organizations have daily, makes Incident Management (IM) process quite demanding. An effective IM system need to enable decision makers to detect problems easily otherwise the organizations can face unscheduled system downtime and/or unplanned costs. By predicting these problems, the decision makers can better allocate resources and mitigate costs. Therefore, this research aims to help predicting those problems by looking at the history of past deployments and incident ticket creation and relate them by using machine learning algorithms to predict the number of incidents of a certain deployment. This research aims to analyze the results with the most used algorithms found in the literature. | eng |
dc.language.iso | eng | - |
dc.publisher | Newswood Limited | - |
dc.relation | CIT INOV-INESC INOVAÇÃO-Financiamento Base | - |
dc.rights | openAccess | - |
dc.subject | Predictive analysis | eng |
dc.subject | Incident management | eng |
dc.subject | Software deployment | eng |
dc.subject | Machine learning | eng |
dc.title | Predictive analysis of incidents based on software deployments | eng |
dc.type | conferenceObject | - |
dc.event.title | World Congress on Engineering | - |
dc.event.type | Conferência | pt |
dc.event.location | London | eng |
dc.event.date | 2019 | - |
dc.pagination | 150 - 155 | - |
dc.peerreviewed | yes | - |
dc.journal | Proceedings of World Congress on Engineering 2019 | - |
degois.publication.firstPage | 150 | - |
degois.publication.lastPage | 155 | - |
degois.publication.location | London | eng |
degois.publication.title | Predictive analysis of incidents based on software deployments | eng |
dc.date.updated | 2021-05-12T11:03:31Z | - |
dc.description.version | info:eu-repo/semantics/publishedVersion | - |
dc.subject.fos | Domínio/Área Científica::Ciências Naturais::Ciências da Computação e da Informação | por |
dc.subject.fos | Domínio/Área Científica::Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática | por |
iscte.identifier.ciencia | https://ciencia.iscte-iul.pt/id/ci-pub-81014 | - |
Aparece nas coleções: | ISTAR-CRI - Comunicações a conferências internacionais |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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conferenceobject_81014.pdf | Versão Editora | 1,06 MB | Adobe PDF | Ver/Abrir |
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