92 citations · 368 across the 16 of their papers we have counts for
16 papers
An Explainable Machine Learning Framework for Railway Predictive Maintenance using Data Streams from the Metro Operator of Portugal
Silvia García-Méndez, Francisco de Arriba-Pérez, Fátima Leal +3
This work contributes to a real-time data-driven predictive maintenance solution for Intelligent Transportation Systems. The proposed method implements a processing pipeline compri…
Promoting Security and Trust on Social Networks: Explainable Cyberbullying Detection Using Large Language Models in a Stream-Based Machine Learning Framework
Silvia García-Méndez, Francisco De Arriba-Pérez
Social media platforms enable instant and ubiquitous connectivity and are essential to social interaction and communication in our technological society. Apart from its advantages,…
Explainable cognitive decline detection in free dialogues with a Machine Learning approach based on pre-trained Large Language Models
Francisco de Arriba-Pérez, Silvia García-Méndez, Javier Otero-Mosquera +1
Cognitive and neurological impairments are very common, but only a small proportion of affected individuals are diagnosed and treated, partly because of the high costs associated w…
Leveraging Large Language Models through Natural Language Processing to provide interpretable Machine Learning predictions of mental deterioration in real time
Francisco de Arriba-Pérez, Silvia García-Méndez
Based on official estimates, 50 million people worldwide are affected by dementia, and this number increases by 10 million new patients every year. Without a cure, clinical prognos…
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…
Automatic detection of cognitive impairment in elderly people using an entertainment chatbot with Natural Language Processing capabilities
Francisco de Arriba-Pérez, Silvia García-Méndez, Francisco J. González-Castaño +1
Previous researchers have proposed intelligent systems for therapeutic monitoring of cognitive impairments. However, most existing practical approaches for this purpose are based o…
Explainable machine learning multi-label classification of Spanish legal judgements
Francisco de Arriba-Pérez, Silvia García-Méndez, Francisco J. González-Castaño +1
Artificial Intelligence techniques such as Machine Learning (ML) have not been exploited to their maximum potential in the legal domain. This has been partially due to the insuffic…
Explainable automatic industrial carbon footprint estimation from bank transaction classification using natural language processing
Jaime González-González, Silvia García-Méndez, Francisco de Arriba-Pérez +2
Concerns about the effect of greenhouse gases have motivated the development of certification protocols to quantify the industrial carbon footprint (CF). These protocols are manual…
A review on the use of large language models as virtual tutors
Silvia García-Méndez, Francisco de Arriba-Pérez, María del Carmen Somoza-López
Transformer architectures contribute to managing long-term dependencies for Natural Language Processing, representing one of the most recent changes in the field. These architectur…
Exposing and Explaining Fake News On-the-Fly
Francisco de Arriba-Pérez, Silvia García-Méndez, Fátima Leal +2
Social media platforms enable the rapid dissemination and consumption of information. However, users instantly consume such content regardless of the reliability of the shared data…
Targeted aspect-based emotion analysis to detect opportunities and precaution in financial Twitter messages
Silvia García-Méndez, Francisco de Arriba-Pérez, Ana Barros-Vila +1
Microblogging platforms, of which Twitter is a representative example, are valuable information sources for market screening and financial models. In them, users voluntarily provid…
Automatic detection of relevant information, predictions and forecasts in financial news through topic modelling with Latent Dirichlet Allocation
Silvia García-Méndez, Francisco de Arriba-Pérez, Ana Barros-Vila +2
Financial news items are unstructured sources of information that can be mined to extract knowledge for market screening applications. Manual extraction of relevant information fro…
Detection of Temporality at Discourse Level on Financial News by Combining Natural Language Processing and Machine Learning
Silvia García-Méndez, Francisco de Arriba-Pérez, Ana Barros-Vila +1
Finance-related news such as Bloomberg News, CNN Business and Forbes are valuable sources of real data for market screening systems. In news, an expert shares opinions beyond plain…
Automatic explanation of the classification of Spanish legal judgments in jurisdiction-dependent law categories with tree estimators
Jaime González-González, Francisco de Arriba-Pérez, Silvia García-Méndez +2
Automatic legal text classification systems have been proposed in the literature to address knowledge extraction from judgments and detect their aspects. However, most of these sys…
Detection of financial opportunities in micro-blogging data with a stacked classification system
Francisco de Arriba-Pérez, Silvia García-Méndez, José A. Regueiro-Janeiro +1
Micro-blogging sources such as the Twitter social network provide valuable real-time data for market prediction models. Investors' opinions in this network follow the fluctuations…
Entertainment chatbot for the digital inclusion of elderly people without abstraction capabilities
Silvia García-Méndez, Francisco de Arriba-Pérez, Francisco J. González-Castaño +2
Current language processing technologies allow the creation of conversational chatbot platforms. Even though artificial intelligence is still too immature to support satisfactory u…