Building a relevance feedback corpus for legal information retrieval in the real-case scenario of the Brazilian Chamber of Deputies.
The proper functioning of judicial and legislative institutions requires the efficient retrieval of legal documents from extensive datasets. Legal Information Retrieval focuses on investigating how to efficiently handle these datasets, enabling the retrieval of pertinent information from them. Relev...
| Publicado en: | Language Resources & Evaluation Vol. 59; no. 2; pp. 1257 - 1278 |
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| Autores principales: | , , , , , , |
| Formato: | Artículo |
| Publicado: |
Springer Nature
Jun2025
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=185240060&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 185240060 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 1574020X 179V jtl: Language Resources & Evaluation issn: 1574020X maglogo: N pubinfo: dt: Jun2025 vid: 59 iid: 2 pid: 237 pub: Springer Nature artinfo: ui: 185240060 10.1007/s10579-024-09767-3 ppf: 1257 ppct: 21 formats: fmt: – @attributes: type: T – @attributes: type: P size: 1.5MB tig: atl: Building a relevance feedback corpus for legal information retrieval in the real-case scenario of the Brazilian Chamber of Deputies. aug: au: Vitório, Douglas Souza, Ellen Martins, Lucas da Silva, Nádia F. F. de Carvalho, André Carlos Ponce de Leon Oliveira, Adriano L. I. de Andrade, Francisco Edmundo affil: https://ror.org/047908t24 Centro de Informática, Universidade Federal de Pernambuco, Recife, Pernambuco, Brazil https://ror.org/02ksmb993 Unidade Acadêmica de Serra Talhada, Universidade Federal Rural de Pernambuco, Serra Talhada, Pernambuco, Brazil https://ror.org/036rp1748 Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo, Sâo Carlos, São Paulo, Brazil https://ror.org/0039d5757 Instituto de Informática, Universidade Federal de Goiás, Goiânia, Goiás, Brazil Câmara dos Deputados, Brasília, Distrito Federal, Brazil su: Information storage & retrieval systems Legal literature Legislative hearings Portuguese language Legal documents Information retrieval sug: subj: Information storage & retrieval systems Legal literature Legislative hearings Portuguese language Legal documents Information retrieval keyword: Brazilian Portuguese Corpus Legal information retrieval Relevance feedback ab: The proper functioning of judicial and legislative institutions requires the efficient retrieval of legal documents from extensive datasets. Legal Information Retrieval focuses on investigating how to efficiently handle these datasets, enabling the retrieval of pertinent information from them. Relevance Feedback, an important aspect of Information Retrieval systems, utilizes the relevance information provided by the user to enhance document retrieval for a specific request. However, there is a lack of available corpora containing this information, particularly for the legislative scenario. Thus, this paper presents Ulysses-RFCorpus, a Relevance Feedback corpus for legislative information retrieval, built in the real-case scenario of the Brazilian Chamber of Deputies. To the best of our knowledge, this corpus is the first publicly available of its kind for the Brazilian Portuguese language. It is also the only corpus that contains feedback information for legislative documents, as the other corpora found in the literature primarily focus on judicial texts. We also used the corpus to evaluate the performance of the Brazilian Chamber of Deputies' Information Retrieval system. Thereby, we highlighted the model's strong performance and emphasized the dataset's significance in the field of Legal Information Retrieval. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Language Resources & Evaluation is a copyright of Springer, 2025. All Rights Reserved. item: Language Resources & Evaluation holder: Springer Nature dt: @attributes: year: 2025 holdings: @attributes: islocal: N |
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