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Association Rule Analysis of Student Satisfaction Surveys for Teaching Quality Evaluation
(Springer Link, 2023-08)
The quality of university teaching is essential for the success of students and the academic excellence of an educational institution. The purpose of this work is to provide a methodology based on the Association Rule ...
Artículo
La Combinación de Sistemas y el PLN
(Sociedad Española para el Procesamiento del Lenguaje Natural (SEPLN), 2010)
La combinación de sistemas constituye un área de investigación ampliamente estudiada en el ámbito del Reconocimiento de Patrones, en donde se han desarrollado múltiples técnicas para aprovechar la diversidad de métodos de ...
Artículo
Generación Semiautomática de Recursos
(Sociedad Española para el Procesamiento del Lenguaje Natural (SEPLN), 2007)
Los resultados de muchos algoritmos que se aplican en tareas de procesamiento del lenguaje natural dependen de la disponibilidad de grandes recursos lingüíısticos, de los que extraen el conocimiento necesario para ...
Artículo
MCFS: Min-cut-based feature-selection
(Elsevier, 2020)
In this paper, MCFS (Min-Cut-based feature-selection) is presented, which is a feature-selection algorithm based on the representation of the features in a dataset by means of a directed graph. The main contribution of our ...
Artículo
Deep Learning Techniques to Improve the Performance of Olive Oil Classification
(Frontiers Editorial, 2020)
The olive oil assessment involves the use of a standardized sensory analysis according to the “panel test” method. However, there is an important interest to design novel strategies based on the use of Gas Chromatography ...
Artículo
An evolutionary approach to estimating software development projects
(Elsevier, 2001)
The use of dynamic models and simulation environments in connection with software projects paved the way for tools that allow us to simulate the behaviour of the projects. The main advantage of a Software Project Simulator ...
Artículo
A new approach based on association rules to add explainability to time series forecasting models
(ScienceDirect, 2023)
Machine learning and deep learning have become the most useful and powerful tools in the last years to mine information from large datasets. Despite the successful application to many research fields, it is widely known ...
Artículo
An empirical analysis of the relationship among price, demand and CO2 emissions in the Spanish electricity market
(Elsevier, 2024)
CO2 emissions play a crucial role in international politics. Countries enter into agreements to reduce the amount of pollution emitted into the atmosphere. Energy generation is one of the main contributors to pollution and ...
Artículo
A comparison of machine learning regression techniques for LiDAR-derived estimation of forest variables
(Elsevier, 2015)
Light Detection and Ranging (LiDAR) is a remote sensor able to extract three-dimensional information. Environmental models in forest areas have been benefited by the use of LiDAR-derived information in the last years. A ...
Artículo
Deep embeddings and Graph Neural Networks: using context to improve domain-independent predictions
(SprigerLink, 2023-06-28)
Graph neural networks (GNNs) are deep learning architectures that apply graph convolutions through message-passing processes between nodes, represented as embeddings. GNNs have recently become popular because of their ...