Document Clustering as an approach to template extraction

Detalhes bibliográficos
Autor(a) principal: Rodrigues, André Miguel Fernandes
Data de Publicação: 2022
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/135877
Resumo: Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business Intelligence
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spelling Document Clustering as an approach to template extractionDocument ClusteringSimilarity MeasuresText RepresentationTemplateNatural Language ProcessingDissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceA great part of customer support is done via the exchange of emails. As the number of emails exchanged daily is constantly increasing, companies need to find approaches to ensure its efficiency. One common strategy is the usage of template emails as an answer. These answers templates are usually found by a human agent through the repetitive usage of the same answer. In this work, we use a clustering approach to find these answer templates. Several clustering algorithms are researched in this work, with a focus on the k-means methodology, as well as other clustering components such as similarity measures and pre-processing steps. As we are dealing with text data, several text representation methods are also compared. Due to the peculiarity of the provided data, we are able to design methodologies to ensure the feasibility of this task and develop strategies to extract the answer templates from the clustering results.Almeida, Mariana Sá Correia Leite deRei, Ricardo Costa DiasRUNRodrigues, André Miguel Fernandes2022-04-05T15:46:03Z2022-04-012022-04-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/135877TID:202988228enginfo: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:RCAAP2023-07-10T16:06:20ZPortal AgregadorONG
dc.title.none.fl_str_mv Document Clustering as an approach to template extraction
title Document Clustering as an approach to template extraction
spellingShingle Document Clustering as an approach to template extraction
Rodrigues, André Miguel Fernandes
Document Clustering
Similarity Measures
Text Representation
Template
Natural Language Processing
title_short Document Clustering as an approach to template extraction
title_full Document Clustering as an approach to template extraction
title_fullStr Document Clustering as an approach to template extraction
title_full_unstemmed Document Clustering as an approach to template extraction
title_sort Document Clustering as an approach to template extraction
author Rodrigues, André Miguel Fernandes
author_facet Rodrigues, André Miguel Fernandes
author_role author
dc.contributor.none.fl_str_mv Almeida, Mariana Sá Correia Leite de
Rei, Ricardo Costa Dias
RUN
dc.contributor.author.fl_str_mv Rodrigues, André Miguel Fernandes
dc.subject.por.fl_str_mv Document Clustering
Similarity Measures
Text Representation
Template
Natural Language Processing
topic Document Clustering
Similarity Measures
Text Representation
Template
Natural Language Processing
description Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business Intelligence
publishDate 2022
dc.date.none.fl_str_mv 2022-04-05T15:46:03Z
2022-04-01
2022-04-01T00:00:00Z
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/10362/135877
TID:202988228
url http://hdl.handle.net/10362/135877
identifier_str_mv TID:202988228
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
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
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collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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