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Artículo
Ampliación automática de corpus mediante la colaboración de varios etiquetadores
(Sociedad Española para el Procesamiento del Lenguaje Natural (SEPLN), 2006)
La disponibilidad de grandes corpus con texto etiquetado es un aspecto esencial en muchas tareas del procesamiento del lenguaje natural. El esfuerzo que se requiere para etiquetar manualmente este gran número de frases ...
Artículo
Ameva: An autonomous discretization algorithm
(ScienceDirect, 2009-04)
This paper describes a new discretization algorithm, called Ameva, which is designed to work with supervised learning algorithms. Ameva maximizes a contingency coefficient based on Chi-square statistics and generates a ...
Artículo
TAPON: a two-phase machine learning approach for semantic labelling
(Elsevier, 2019-01-01)
Through semantic labelling we enrich structured information from sources such as HTML pages, tables, or JSON files, with labels to integrate it into a local ontology. This process involves measuring some features of the ...
Artículo
Comparing artificial intelligence strategies for early sepsis detection in the ICU: an experimental study
(Springer, 2023)
Sepsis is a life-threatening condition whose early recognition is key to improving outcomes for patients in intensive care units (ICUs). Artificial intelligence can play a crucial role in mining and exploiting health data ...
Ponencia
Using Machine Learning to Infer Constraints for Product Lines
(ACM, 2016)
Variability intensive systems may include several thousand features allowing for an enormous number of possible configurations, including wrong ones (e.g. the derived product does not compile). For years, engineers have ...
Ponencia
Artículo
TAPON-MT: a versatile framework for semantic labelling
(Elsevier, 2019-07)
Semantic labelling refers to the problem of assigning known labels to the elements of structured information from a source such as an HTML table or an RDF dump with unknown semantics. In the recent years it has become ...
Artículo
Detecting Flight Trajectory Anomalies and Predicting Diversions in Freight Transportation
(Elsevier, 2016)
Timely identifying flight diversions is a crucial aspect of efficient multi-modal transportation. When an airplane diverts, logistics providers must promptly adapt their transportation plans in order to ensure proper ...
Capítulo de Libro
Data streams classification by incremental rule learning with parameterized generalization
(2006)
Mining data streams is a challenging task that requires online systems based on incremental learning approaches. This paper describes a classification system based on decision rules that may store up--to--date border ...
Artículo
Enhancing smart home appliance recognition with wavelet and scalogram analysis using data augmentation
(IOS Press, 2024)
The development of smart homes, equipped with devices connected to the Internet of Things (IoT), has opened up new possibilities to monitor and control energy consumption. In this context, non-intrusive load monitoring ...