Automatization of incident categorization
Autor(a) principal: | |
---|---|
Data de Publicação: | 2018 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10071/17585 |
Resumo: | To be able to keep up with the grow of the created incidents quantity in an organization nowadays, there was the need to increase the resources to ensure the management of all incidents. Incident Management is composed by several activities, being one of them, Incident Categorization. Merging Natural Language and Text Mining techniques and Machine Learning algorithms, we propose improve this activity, specifically the Incident Management Process. For that, we propose replace the manual sub-process of Categorization inherent to the Incident Management Process by an automatic sub-process, without any human interaction. The goal of this dissertation is to propose a solution to categorize correctly and automatically the incidents. For that, there are real data provided by a company, which due to privacy questions will not be mention along dissertation. The datasets are composed by incidents correctly categorized, which leverage us to apply supervised learning algorithms. It is supposed to obtain as output a developed method through the merge of Natural Language Processing techniques and classification algorithms with better performance on the data. At the end, the proposed method is assessed comparatively with the current categorization done to conclude if our proposal really improves the Incident Management Process and which are the advantages brought by the automation. |
id |
RCAP_816eebb09267c388dc2a9fd64f73b163 |
---|---|
oai_identifier_str |
oai:repositorio.iscte-iul.pt:10071/17585 |
network_acronym_str |
RCAP |
network_name_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository_id_str |
7160 |
spelling |
Automatization of incident categorizationAutomated incident categorizationIncident categorizationIncident management processMachine learningNatural languageText miningEngenharia informáticaGestão da informaçãoCategorizaçãoLinguagem naturalProcessamento de textoAlgoritmo de aprendizagemTo be able to keep up with the grow of the created incidents quantity in an organization nowadays, there was the need to increase the resources to ensure the management of all incidents. Incident Management is composed by several activities, being one of them, Incident Categorization. Merging Natural Language and Text Mining techniques and Machine Learning algorithms, we propose improve this activity, specifically the Incident Management Process. For that, we propose replace the manual sub-process of Categorization inherent to the Incident Management Process by an automatic sub-process, without any human interaction. The goal of this dissertation is to propose a solution to categorize correctly and automatically the incidents. For that, there are real data provided by a company, which due to privacy questions will not be mention along dissertation. The datasets are composed by incidents correctly categorized, which leverage us to apply supervised learning algorithms. It is supposed to obtain as output a developed method through the merge of Natural Language Processing techniques and classification algorithms with better performance on the data. At the end, the proposed method is assessed comparatively with the current categorization done to conclude if our proposal really improves the Incident Management Process and which are the advantages brought by the automation.De forma a acompanhar o crescimento da quantidade de incidentes criados no diaa-dia de uma organização, houve a necessidade de aumentar a quantidade de recursos, de maneira a assegurar a gestão de todos os incidentes. A gestão de incidentes é composta por várias atividades, sendo uma delas, a categorização de incidentes. Através da junção de técnicas de Linguagem Natural e Processamento de Texto e de Algoritmos de Aprendizagem Automática propomos melhorar esta atividade, especificamente o Processo de Gestão de Incidentes. Para tal, propomos a substituição do subprocesso manual de Categorização inerente ao Processo de Gestão de Incidentes por um subprocesso automatizado, sem qualquer interação humana. A dissertação tem como objetivo propor uma solução para categorizar corretamente e automaticamente incidentes. Para tal, temos dados reais de uma organização, que devido a questões de privacidade não será mencionada ao longo da dissertação. Os datasets são compostos por incidentes corretamente categorizados o que nos leva a aplicar algoritmos de aprendizagem supervisionada. Pretendemos ter como resultado final um método desenvolvido através da junção das diferentes técnicas de Linguagem Natural e dos algoritmos com melhor performance para classificar os dados. No final será avaliado o método proposto comparativamente à categorização que é realizada atualmente, de modo a concluir se a nossa proposta realmente melhora o Processo de Gestão de Incidentes e quais são as vantagens trazidas pela automatização.2019-03-13T13:23:53Z2018-12-04T00:00:00Z2018-12-042018-09info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfapplication/octet-streamhttp://hdl.handle.net/10071/17585TID:202133869engSilva, Sara Alexandra Teixeira dainfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-09T17:25:50Zoai:repositorio.iscte-iul.pt:10071/17585Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:11:32.034186Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Automatization of incident categorization |
title |
Automatization of incident categorization |
spellingShingle |
Automatization of incident categorization Silva, Sara Alexandra Teixeira da Automated incident categorization Incident categorization Incident management process Machine learning Natural language Text mining Engenharia informática Gestão da informação Categorização Linguagem natural Processamento de texto Algoritmo de aprendizagem |
title_short |
Automatization of incident categorization |
title_full |
Automatization of incident categorization |
title_fullStr |
Automatization of incident categorization |
title_full_unstemmed |
Automatization of incident categorization |
title_sort |
Automatization of incident categorization |
author |
Silva, Sara Alexandra Teixeira da |
author_facet |
Silva, Sara Alexandra Teixeira da |
author_role |
author |
dc.contributor.author.fl_str_mv |
Silva, Sara Alexandra Teixeira da |
dc.subject.por.fl_str_mv |
Automated incident categorization Incident categorization Incident management process Machine learning Natural language Text mining Engenharia informática Gestão da informação Categorização Linguagem natural Processamento de texto Algoritmo de aprendizagem |
topic |
Automated incident categorization Incident categorization Incident management process Machine learning Natural language Text mining Engenharia informática Gestão da informação Categorização Linguagem natural Processamento de texto Algoritmo de aprendizagem |
description |
To be able to keep up with the grow of the created incidents quantity in an organization nowadays, there was the need to increase the resources to ensure the management of all incidents. Incident Management is composed by several activities, being one of them, Incident Categorization. Merging Natural Language and Text Mining techniques and Machine Learning algorithms, we propose improve this activity, specifically the Incident Management Process. For that, we propose replace the manual sub-process of Categorization inherent to the Incident Management Process by an automatic sub-process, without any human interaction. The goal of this dissertation is to propose a solution to categorize correctly and automatically the incidents. For that, there are real data provided by a company, which due to privacy questions will not be mention along dissertation. The datasets are composed by incidents correctly categorized, which leverage us to apply supervised learning algorithms. It is supposed to obtain as output a developed method through the merge of Natural Language Processing techniques and classification algorithms with better performance on the data. At the end, the proposed method is assessed comparatively with the current categorization done to conclude if our proposal really improves the Incident Management Process and which are the advantages brought by the automation. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-12-04T00:00:00Z 2018-12-04 2018-09 2019-03-13T13:23:53Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10071/17585 TID:202133869 |
url |
http://hdl.handle.net/10071/17585 |
identifier_str_mv |
TID:202133869 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf application/octet-stream |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
|
_version_ |
1799134669969555456 |