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acessibilidade

http://hdl.handle.net/10071/16690
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acessibilidade
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dc.contributor.authorSilva, S.-
dc.contributor.authorRibeiro, R.-
dc.contributor.authorPereira, R.-
dc.contributor.editorPedro Rangel Henriques; José Paulo Leal; António Menezes Leitão; Xavier Gómez Guinovart-
dc.date.accessioned2018-10-17T16:39:24Z-
dc.date.available2018-10-17T16:39:24Z-
dc.date.issued2018-
dc.identifier.isbn978-3-95977-072-9-
dc.identifier.issn2190-6807-
dc.identifier.urihttps://ciencia.iscte-iul.pt/id/ci-pub-50350-
dc.identifier.urihttp://hdl.handle.net/10071/16690-
dc.description.abstractThe IT incident management process requires a correct categorization to attribute incident tickets to the right resolution group and obtain as quickly as possible an operational system, impacting the minimum as possible the business and costumers. In this work, we introduce automatic text classification, demonstrating the application of several natural language processing techniques and analyzing the impact of each one on a real incident tickets dataset. The techniques that we explore in the pre-processing of the text that describes an incident are the following: tokenization, stemming, eliminating stop-words, named-entity recognition, and TFxIDF-based document representation. Finally, to build the model and observe the results after applying the previous techniques, we use two machine learning algorithms: Support Vector Machine (SVM) and K-Nearest Neighbor (KNN). Two important findings result from this study: a shorter description of an incident is better than a full description of an incident; and, pre-processing has little impact on incident categorization, mainly due the specific vocabulary used in this type of text.eng
dc.language.isoeng-
dc.publisherSchloss Dagstuhl--Leibniz-Zentrum fuer Informatik-
dc.rightsopenAccess-
dc.subjectMachine learningeng
dc.subjectAutomated incident categorizationeng
dc.subjectSVMeng
dc.subjectIncident managementeng
dc.subjectNatural languageeng
dc.titleLess is more in incident categorizationeng
dc.typeconferenceObject-
dc.event.typeConferênciapt
dc.event.locationGuimarãeseng
dc.event.date2018-
dc.peerreviewedyes-
dc.journal7th Symposium on Languages, Applications and Technologies, SLATE-
dc.volume62-
degois.publication.locationGuimarãeseng
degois.publication.titleLess is more in incident categorizationeng
dc.description.versioninfo:eu-repo/semantics/publishedVersion-
dc.identifier.doi10.4230/OASIcs.SLATE.2018.17-
dc.subject.fosDomínio/Área Científica::Ciências Naturais::Ciências da Computação e da Informaçãopor
dc.subject.fosDomínio/Área Científica::Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informáticapor
Appears in Collections:ISTAR-CRI - Comunicações a conferências internacionais

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