https://repositorio.ufu.br/handle/123456789/17903 2026-08-08T04:39:23Z 2026-08-08T04:39:23Z https://repositorio.ufu.br/handle/123456789/49367 2026-08-07T16:47:55Z 2025-09-25T00:00:00Z

Title: Projeto de plataforma para gestão de programas de habitação de interesse social: Minha Casa, Minha Vida - Faixa 1 Abstract: This work presents the development and prototyping of a web platform aimed at managing social housing processes, with a specific focus on Faixa 1 of the Minha Casa, Minha Vida Program (PMCMV). The identified problem is the lack of integrated systems in municipalities, especially small and medium-sized ones, to standardize, track, and efficiently operate the stages of application, evaluation, and contracting of program beneficiaries, which compromises the transparency and effectiveness of housing initiatives. Thus, a modular digital solution is proposed, adaptable to current legislation and municipal realities, in order to significantly improve the management of these processes. The platform was modeled based on real workflows observed in municipal public administrations. In addition, two modules (Application and Evaluation) were implemented, and a third (Contracting) was modeled, meeting the defined functional and non-functional requirements. The results indicate the technical feasibility of the solution, with potential practical application in public administration, contributing to the transparency, traceability, and efficiency of PMCMV Faixa 1 processes.

2025-09-25T00:00:00Z https://repositorio.ufu.br/handle/123456789/49252 2026-08-04T06:21:36Z 2026-05-08T00:00:00Z

Title: Avaliação de diferentes metodologias para o ensino de computação gráfica em nível superior

2026-05-08T00:00:00Z https://repositorio.ufu.br/handle/123456789/49189 2026-07-31T06:23:40Z 2026-03-26T00:00:00Z

Title: Avaliação de modelos de processamento de linguagem natural para análise de sentimentos em avaliações de restaurantes Abstract: The food sector has a significant impact on the Brazilian economy, and with the digitalization of how society seeks information about establishments, review platforms like Google Maps have become crucial in consumer perception and decision-making. However, simply viewing overall star ratings masks important nuances in customer sentiment and hinders the extraction of detailed metrics from large volumes of text. To address this gap, this study evaluates the performance of different Natural Language Processing (NLP) models in the task of sentiment analysis in Google Maps restaurant reviews. To this end, the methodology consisted of automated data collection (Web Scraping) from establishment pages on Google Maps, followed by processing the textual review database using the BERT, XLM-ROBERTa, and LeIA models. The results demonstrated that the BERT model showed the best suitability for direct comparisons with user ratings. XLM-ROBERTa, in turn, demonstrated high reliability, although its categorical classification limited precision in numerical comparisons. The LeIA model, despite using a more classical lexical approach, produced consistent results comparable to the others. Furthermore, the analysis revealed a behavioral disparity: the sentiment polarity extracted exclusively from the texts tended to be lower than the establishment's overall rating. It is concluded that the application of Natural Language Processing models provides complementary metrics that can be useful for the management of gastronomic businesses, overcoming the analytical limitations of ratings based solely on stars.

2026-03-26T00:00:00Z https://repositorio.ufu.br/handle/123456789/49073 2026-07-25T06:27:45Z 2026-03-10T00:00:00Z

Title: Aplicação de técnicas de mineração de dados para identificação de padrões de vendas em marketplaces

2026-03-10T00:00:00Z