activity
20152026
most citedA Survey on Domain-Specific Languages for Machine Learning in Big Data

5 citations · 12 across the 7 of their papers we have counts for

collaborators

8 papers

cs.AI2026

CPEMH: An Agentic Framework for Prompt-Driven Behavior Evaluation and Assurance in Foundation-Model Systems for Mental Health Screening

Giuliano Lorenzoni, Ivens Portugal, Paulo Alencar +1

This paper presents CPEMH, an agentic framework designed to evaluate prompt-driven behavior in foundation-model systems operating on transcript-based datasets for mental-health scr…

cs.CL2024

Exploring Variability in Fine-Tuned Models for Text Classification with DistilBERT

Giuliano Lorenzoni, Ivens Portugal, Paulo Alencar +1

This study evaluates fine-tuning strategies for text classification using the DistilBERT model, specifically the distilbert-base-uncased-finetuned-sst-2-english variant. Through st…

cs.DB2019★ 1 cited

Spatial-Temporal Cluster Relations -- A Foundation for Trajectory Cluster Lifetime Analysis

Ivens Portugal, Paulo Alencar, Donald Cowan

Spatial-temporal data, that is information about objects that exist at a particular location and time period, are rich in value and, as a consequence, the target of so many initiat…

cs.CY2018

Cluster Lifecycle Analysis: Challenges, Techniques, and Framework

Ivens Portugal, Paulo Alencar, Donald Cowan

Novel forms of data analysis methods have emerged as a significant research direction in the transportation domain. These methods can potentially help to improve our understanding…

cs.DB2017★ 3 cited

Developing a Spatial-Temporal Contextual and Semantic Trajectory Clustering Framework

Ivens Portugal, Paulo Alencar, Donald Cowan

This paper reports on ongoing research investigating more expressive approaches to spatial-temporal trajectory clustering. Spatial-temporal data is increasingly becoming universal…

cs.SE2016★ 5 cited

A Survey on Domain-Specific Languages for Machine Learning in Big Data

Ivens Portugal, Paulo Alencar, Donald Cowan

The amount of data generated in the modern society is increasing rapidly. New problems and novel approaches of data capture, storage, analysis and visualization are responsible for…

cs.SE2015

The Use of Machine Learning Algorithms in Recommender Systems: A Systematic Review

Ivens Portugal, Paulo Alencar, Donald Cowan

Recommender systems use algorithms to provide users with product or service recommendations. Recently, these systems have been using machine learning algorithms from the field of a…

cs.SE2015★ 3 cited

Requirements Engineering for General Recommender Systems

Ivens Portugal, Paulo Alencar, Donald Cowan

In requirements engineering for recommender systems, software engineers must identify the data that drives the recommendations. This is a labor-intensive task, which is error-prone…