Proceendings of 19th National Meeting on Artificial and Computational Intelligence (2022)
- Authors:
- Autor USP: MARCACINI, RICARDO MARCONDES - ICMC
- Unidade: ICMC
- DOI: 10.5753/eniac.2022
- Assunto: INTELIGÊNCIA ARTIFICIAL
- Language: Inglês
- Imprenta:
- Publisher: SBC
- Publisher place: Porto Alegre
- Date published: 2022
- Source:
- ISSN: 2763-9061
- Conference titles: Encontro Nacional de Inteligência Artificial e Computacional - ENIAC
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
Proceendings of 19th National Meeting on Artificial and Computational Intelligence. . Porto Alegre: SBC. Disponível em: https://doi.org/10.5753/eniac.2022. Acesso em: 17 fev. 2026. , 2022 -
APA
Proceendings of 19th National Meeting on Artificial and Computational Intelligence. (2022). Proceendings of 19th National Meeting on Artificial and Computational Intelligence. Porto Alegre: SBC. doi:10.5753/eniac.2022 -
NLM
Proceendings of 19th National Meeting on Artificial and Computational Intelligence [Internet]. 2022 ;[citado 2026 fev. 17 ] Available from: https://doi.org/10.5753/eniac.2022 -
Vancouver
Proceendings of 19th National Meeting on Artificial and Computational Intelligence [Internet]. 2022 ;[citado 2026 fev. 17 ] Available from: https://doi.org/10.5753/eniac.2022 - Complaint analysis in fintech domain: a case study in Brazilian brokerage firms
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- Aprendizado não supervisionado de hierarquias de tópicos a partir de coleções textuais dinâmicas
- MApp-IDEA: design and architecture of the analytical data exploration tool from app reviews
- PPM-HC: a method for helping project portfolio management based on topic hierarchy learnings
- Named Entity Recognition approaches applied to legal document segmentation
- Opinion mining for App reviews: identifying and prioritizing emerging issues for software maintenance and evolution
- Characterization of co-authorship networks of CNPq productivity fellows: an approach based on data science
- iRisk: a scalable microservice for classifying issue risks based on crowdsourced App reviews
- Monitoring temporal dynamics of issues in crowdsourced user reviews and their impact on mobile App updates
Informações sobre o DOI: 10.5753/eniac.2022 (Fonte: oaDOI API)
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