Publicação
INCM & Nova Sbe PBL project - retirement law query system: using top ranking to improve user experience in a semantic search system
| datacite.subject.fos | Ciências Sociais::Economia e Gestão | pt_PT |
| dc.contributor.advisor | Xufre, Patrícia | |
| dc.contributor.advisor | Magalhães, João | |
| dc.contributor.author | Cardoso, Diogo Nasser | |
| dc.date.accessioned | 2022-07-29T10:30:08Z | |
| dc.date.available | 2022-07-29T10:30:08Z | |
| dc.date.issued | 2022-01-20 | |
| dc.date.submitted | 2021-12-17 | |
| dc.description.abstract | 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. | pt_PT |
| dc.identifier.tid | 203022211 | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10362/142633 | |
| dc.language.iso | eng | pt_PT |
| dc.relation | Nova School of Business and Economics | |
| dc.subject | Machine learning | pt_PT |
| dc.subject | Business analytics | pt_PT |
| dc.subject | Natural language processing | pt_PT |
| dc.subject | Chatbot | pt_PT |
| dc.subject | Nlp | pt_PT |
| dc.subject | Incm | pt_PT |
| dc.subject | Bert | pt_PT |
| dc.subject | Haystack | pt_PT |
| dc.subject | Law query system | pt_PT |
| dc.subject | Semantic search | pt_PT |
| dc.subject | Feedback | pt_PT |
| dc.subject | Top ranking | pt_PT |
| dc.subject | User experience | pt_PT |
| dc.subject | Retirement law | pt_PT |
| dc.subject | Big data analysis | pt_PT |
| dc.title | INCM & Nova Sbe PBL project - retirement law query system: using top ranking to improve user experience in a semantic search system | pt_PT |
| dc.type | master thesis | |
| dspace.entity.type | Publication | |
| oaire.awardNumber | UID/ECO/00124/2013 | |
| oaire.awardTitle | Nova School of Business and Economics | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UID%2FECO%2F00124%2F2013/PT | |
| oaire.fundingStream | 6817 - DCRRNI ID | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | masterThesis | pt_PT |
| relation.isProjectOfPublication | 644a3f4f-817b-4d0d-aba6-f98cdca28bc7 | |
| relation.isProjectOfPublication.latestForDiscovery | 644a3f4f-817b-4d0d-aba6-f98cdca28bc7 | |
| thesis.degree.name | A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics | pt_PT |