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7 papers · 1 filter
Explainable Anomaly Detection for Industrial IoT Data Streams
Ana Rita Paupério, Diogo Risca, Afonso Lourenço +2
Industrial maintenance is being transformed by the Internet of Things and edge computing, generating continuous data streams that demand real-time, adaptive decision-making under l…
Online hierarchical partitioning of the output space in extreme multi-label data stream
Lara Neves, Afonso Lourenço, Alberto Cano +1
Mining data streams with multi-label outputs poses significant challenges due to evolving distributions, high-dimensional label spaces, sparse label occurrences, and complex label…
In-context Learning of Evolving Data Streams with Tabular Foundational Models
Afonso Lourenço, João Gama, Eric P. Xing +1
State-of-the-art data stream mining has long drawn from ensembles of the Very Fast Decision Tree, a seminal algorithm honored with the 2015 KDD Test-of-Time Award. However, the eme…
Online detection and infographic explanation of spam reviews with data drift adaptation
Francisco de Arriba-Pérez, Silvia García-Méndez, Fátima Leal +2
Spam reviews are a pervasive problem on online platforms due to its significant impact on reputation. However, research into spam detection in data streams is scarce. Another conce…
CityLearn v2: Energy-flexible, resilient, occupant-centric, and carbon-aware management of grid-interactive communities
Kingsley Nweye, Kathryn Kaspar, Giacomo Buscemi +12
As more distributed energy resources become part of the demand-side infrastructure, it is important to quantify the energy flexibility they provide on a community scale, particular…
From Data to Action: Exploring AI and IoT-driven Solutions for Smarter Cities
Tiago Dias, Tiago Fonseca, João Vitorino +3
The emergence of smart cities demands harnessing advanced technologies like the Internet of Things (IoT) and Artificial Intelligence (AI) and promises to unlock cities' potential t…