Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/74782
Registo completo
Campo DC | Valor | Idioma |
---|---|---|
dc.contributor.author | Cunha, Luís Filipe da Costa | por |
dc.contributor.author | Ramalho, José Carlos | por |
dc.date.accessioned | 2021-11-26T10:05:56Z | - |
dc.date.available | 2021-11-26T10:05:56Z | - |
dc.date.issued | 2021-09-13 | - |
dc.identifier.issn | 1613-0073 | - |
dc.identifier.uri | https://hdl.handle.net/1822/74782 | - |
dc.description.abstract | The amount of information present in Portuguese archives has been increasing exponentially over the years. At the moment, the majority of the data is already available to the public in digital format, however, the records are stored as unstructured text, making its data processing challenging. In this way, it is intended to perform a semantic interpretation of these documents through the identification and classification of Named Entities. For this purpose, the use of Natural Language Processing tools is proposed, training Machine Learning algorithms capable of accurately recognizing entities in this context. Finally, it is presented a Web platform that implements all the models trained in this paper, as well as some tools that gave support to the entity extraction process. | por |
dc.description.sponsorship | (undefined) | por |
dc.language.iso | eng | por |
dc.publisher | CEUR-Ws | por |
dc.rights | openAccess | por |
dc.rights.uri | http://creativecommons.org/licenses/by-sa/4.0/ | por |
dc.subject | Archival Descriptions | por |
dc.subject | Named Entity Recognition | por |
dc.subject | Machine Learning | por |
dc.subject | Web | por |
dc.title | Towards Entity Linking, NER in archival finding aids | por |
dc.type | conferencePaper | por |
dc.peerreviewed | yes | por |
dc.relation.publisherversion | http://ceur-ws.org/Vol-3019/LinkedArchives_2021_paper_12.pdf | por |
oaire.citationStartPage | 22 | por |
oaire.citationEndPage | 29 | por |
oaire.citationConferencePlace | Online | por |
oaire.citationVolume | 3019 | por |
dc.subject.fos | Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática | por |
sdum.journal | CEUR Workshop Proceedings | por |
sdum.conferencePublication | Linked Archives 2021: proceedings of Linked Archives International Workshop 2021 | por |
oaire.version | VoR | por |
Aparece nas coleções: |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
---|---|---|---|---|
LinkedArchives_2021_paper_12.pdf | artigo | 448,89 kB | Adobe PDF | Ver/Abrir |
Este trabalho está licenciado sob uma Licença Creative Commons