117 citations · 242 across the 21 of their papers we have counts for
5 papers · 1 filter
Concept Drift Adaptation in Text Stream Mining Settings: A Systematic Review
Cristiano Mesquita Garcia, Ramon Simoes Abilio, Alessandro Lameiras Koerich +2
The society produces textual data online in several ways, e.g., via reviews and social media posts. Therefore, numerous researchers have been working on discovering patterns in tex…
Random Forest Kernel for High-Dimension Low Sample Size Classification
Lucca Portes Cavalheiro, Simon Bernard, Jean Paul Barddal +1
High dimension, low sample size (HDLSS) problems are numerous among real-world applications of machine learning. From medical images to text processing, traditional machine learnin…
Detecting Relevant Information in High-Volume Chat Logs: Keyphrase Extraction for Grooming and Drug Dealing Forensic Analysis
Jeovane Honório Alves, Horácio A. C. G. Pedroso, Rafael Honorio Venetikides +4
The growing use of digital communication platforms has given rise to various criminal activities, such as grooming and drug dealing, which pose significant challenges to law enforc…
Deep Single Models vs. Ensembles: Insights for a Fast Deployment of Parking Monitoring Systems
Andre Gustavo Hochuli, Jean Paul Barddal, Gillian Cezar Palhano +2
Searching for available parking spots in high-density urban centers is a stressful task for drivers that can be mitigated by systems that know in advance the nearest parking space…
Advances on Concept Drift Detection in Regression Tasks using Social Networks Theory
Jean Paul Barddal, Heitor Murilo Gomes, Fabrício Enembreck
Mining data streams is one of the main studies in machine learning area due to its application in many knowledge areas. One of the major challenges on mining data streams is concep…