INCM & Nova Sbe PBL project - retirement law query system: using top ranking to improve user experience in a semantic search system

Detalhes bibliográficos
Autor(a) principal: Cardoso, Diogo Nasser
Data de Publicação: 2021
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/142633
Resumo: This study measures how Portuguese BERT performs as a semantic search system for the Portuguese Retirement Law by comparing the proposed solution answers with a test set. The study also envision edhowa feedback method (Top-Ranking)would be implemented in the developed system. This solution aimed to reorder the questions returned by the mode l based on semantic similarity. The semantic search solution showed positive results, but the Top-Ranking method failed to be implemented as the metric for semantic similarity delivered inconsistent results, thus failing to provide a solid structure for such system. The client showed very positive feedback regarding the developed tool, especially when comparing it with the current implemented solution. This project showed that Portuguese BERT is a tool with a lot of potential for semantic search on various other domains.
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spelling INCM & Nova Sbe PBL project - retirement law query system: using top ranking to improve user experience in a semantic search systemMachine learningBusiness analyticsNatural language processingChatbotNlpIncmBertHaystackLaw query systemSemantic searchFeedbackTop rankingUser experienceRetirement lawBig data analysisDomínio/Área Científica::Ciências Sociais::Economia e GestãoThis study measures how Portuguese BERT performs as a semantic search system for the Portuguese Retirement Law by comparing the proposed solution answers with a test set. The study also envision edhowa feedback method (Top-Ranking)would be implemented in the developed system. This solution aimed to reorder the questions returned by the mode l based on semantic similarity. The semantic search solution showed positive results, but the Top-Ranking method failed to be implemented as the metric for semantic similarity delivered inconsistent results, thus failing to provide a solid structure for such system. The client showed very positive feedback regarding the developed tool, especially when comparing it with the current implemented solution. This project showed that Portuguese BERT is a tool with a lot of potential for semantic search on various other domains.Xufre, PatríciaMagalhães, JoãoRUNCardoso, Diogo Nasser2022-07-29T10:30:08Z2022-01-202021-12-172022-01-20T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/142633TID:203022211enginfo: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:RCAAP2024-03-11T05:20:28Zoai:run.unl.pt:10362/142633Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:50:26.607149Repositório 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 INCM & Nova Sbe PBL project - retirement law query system: using top ranking to improve user experience in a semantic search system
title INCM & Nova Sbe PBL project - retirement law query system: using top ranking to improve user experience in a semantic search system
spellingShingle INCM & Nova Sbe PBL project - retirement law query system: using top ranking to improve user experience in a semantic search system
Cardoso, Diogo Nasser
Machine learning
Business analytics
Natural language processing
Chatbot
Nlp
Incm
Bert
Haystack
Law query system
Semantic search
Feedback
Top ranking
User experience
Retirement law
Big data analysis
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
title_short INCM & Nova Sbe PBL project - retirement law query system: using top ranking to improve user experience in a semantic search system
title_full INCM & Nova Sbe PBL project - retirement law query system: using top ranking to improve user experience in a semantic search system
title_fullStr INCM & Nova Sbe PBL project - retirement law query system: using top ranking to improve user experience in a semantic search system
title_full_unstemmed INCM & Nova Sbe PBL project - retirement law query system: using top ranking to improve user experience in a semantic search system
title_sort INCM & Nova Sbe PBL project - retirement law query system: using top ranking to improve user experience in a semantic search system
author Cardoso, Diogo Nasser
author_facet Cardoso, Diogo Nasser
author_role author
dc.contributor.none.fl_str_mv Xufre, Patrícia
Magalhães, João
RUN
dc.contributor.author.fl_str_mv Cardoso, Diogo Nasser
dc.subject.por.fl_str_mv Machine learning
Business analytics
Natural language processing
Chatbot
Nlp
Incm
Bert
Haystack
Law query system
Semantic search
Feedback
Top ranking
User experience
Retirement law
Big data analysis
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
topic Machine learning
Business analytics
Natural language processing
Chatbot
Nlp
Incm
Bert
Haystack
Law query system
Semantic search
Feedback
Top ranking
User experience
Retirement law
Big data analysis
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
description This study measures how Portuguese BERT performs as a semantic search system for the Portuguese Retirement Law by comparing the proposed solution answers with a test set. The study also envision edhowa feedback method (Top-Ranking)would be implemented in the developed system. This solution aimed to reorder the questions returned by the mode l based on semantic similarity. The semantic search solution showed positive results, but the Top-Ranking method failed to be implemented as the metric for semantic similarity delivered inconsistent results, thus failing to provide a solid structure for such system. The client showed very positive feedback regarding the developed tool, especially when comparing it with the current implemented solution. This project showed that Portuguese BERT is a tool with a lot of potential for semantic search on various other domains.
publishDate 2021
dc.date.none.fl_str_mv 2021-12-17
2022-07-29T10:30:08Z
2022-01-20
2022-01-20T00:00:00Z
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/10362/142633
TID:203022211
url http://hdl.handle.net/10362/142633
identifier_str_mv TID:203022211
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
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
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