Mostrando ítems 21-40 de 67

    • ChatGPT and the potential growing of ghost bibliographic references 

      Orduña-Malea, Enrique; Cabezas-Clavijo, Álvaro (Scientometrics, 2023)
      This letter warns about the identification of research publications available online that contain references to non-existent papers (ghost bibliographic references). This is likely to happen due to the use of ChatGPT, a ...
    • Clustering analysis for automatic certification of LMS strategies in a university virtual campus 

      Regueras, Luisa M; Verdú, María J; Castro, Juan P de; Verdú, Elena (IEEE Access, 2019)
      In recent years, the use of Learning Management Systems (LMS) has grown considerably. This has had a strong effect on the learning process, particularly in higher education. Most universities incorporate LMS as a complement ...
    • Cognitive Evaluation of Examinees by Dynamic Question Set Generation based on Bloom’s Taxonomy 

      Dutta, Anjan; Chatterjee, Punyasha; Dey, Nilanjan; Moreno-Ger, Pablo; Sen, Soumya (IETE Journal of Research, 2023)
      Educational data mining (EDM) is an emerging topic in recent years steered by data mining and machine learning techniques to enhance students’ overall learning experience and academic progress. In recent years EDM techniques ...
    • Comparative analysis of paraphrasing performanceof ChatGPT, GPT-3, and T5 language modelsusing a new ChatGPT generated dataset: ParaGPT 

      Pehlivanoglu, Meltem Kurt; Abdan Syakura, Muhammad; de-la-Fuente-Valentín, Luis; Tadesse Gobosho, Robera; Shanmuganathan, Vimal (Expert Systems, 2024)
      Paraphrase generation is a fundamental natural language processing (NLP) task that refers to the process of generating a well-formed and coherent output sentence that exhibits both syntactic and/or lexical diversity from ...
    • CompareML: A Novel Approach to Supporting Preliminary Data Analysis Decision Making 

      Fernández-García, Antonio Jesús; Preciado, Juan Carlos; Prieto, Álvaro E.; Sánchez-Figueroa, Fernando; Gutiérrez, Juan D. (International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI), 06/2022)
      There are a large number of machine learning algorithms as well as a wide range of libraries and services that allow one to create predictive models. With machine learning and artificial intelligence playing a major role ...
    • Connection between sleeping patterns and cognitive deterioration in women with Alzheimer’s disease 

      Corbi, Alberto ; Burgos, Daniel (Springer Science and Business Media Deutschland GmbH, 2022)
      Background: Alzheimer’s disease (AD) causes symptoms such as dementia, memory loss, disorientation, and even aggressiveness, and is more common in women than in men. AD may also manifest itself in changes in sleep patterns. ...
    • Creating a Recommender System to Support Higher Education Students in the Subject Enrollment Decision 

      Fernández-García, Antonio Jesús ; Rodríguez-Echeverría, Roberta; Preciado, Juan Carlos; Conejero Manzano, José María; Sánchez-Figueroa, Fernando (IEEE Access, 2020)
      Higher Education plays a principal role in the changing and complex world of today, and there has been rapid growth in the scientific literature dedicated to predicting students academic success or risk of dropout thanks ...
    • Cross-jurisdictional factors linked to gambling frequency in adolescents from 28 European countries: a machine learning approach 

      Testa, Giulia; Ruiz-Iniesta, Almudena; García García, Óscar; Tarragón, Ernesto; Soriano, Vicente; Benedetti, Elisa; Cerrai, Sonia; Molinaro, Sabrina; Brand, Matthias; Potenza, Marc N.; Mestre-Bach, Gemma (Psychiatry Research, 2025)
      Adolescents are vulnerable to experiencing problematic gambling, although its prevalence and potential risk factors vary across countries. This study aims to identify cross-jurisdictional factors associated with higher ...
    • Detecting Malware in Cyberphysical Systems Using Machine Learning: a Survey 

      Montes, F. ; Bermejo-Higuera, Javier ; Sanchez, L. E.; Bermejo Higuera, Juan Ramón ; Sicilia, Juan Antonio (KSII transactions on internet and information systems, 2021)
      Among the scientific literature, it has not been possible to find a consensus on the definition of the limits or properties that allow differentiating or grouping the cyber-physical systems (CPS) and the Internet of Things ...
    • Determinación automática de los límites de Atterberg con machine learning 

      Rosas, David Antonio; Burgos, Daniel; Branch, John W.; Corbi, Alberto (DYNA, 2022)
      En este estudio, determinamos el límite líquido (𝑊𝑙), el índice de plasticidad (PI) y el límite plástico (𝑊𝑝) de suelos naturales finos con ayuda de machine-learning y métodos estadísticos. Ello permite localizarlos ...
    • ERBM-SE: Extended Restricted Boltzmann Machine for Multi-Objective Single-Channel Speech Enhancement 

      Khattak, Muhammad Irfan; Saleem, Nasir; Nawaz, Aamir; Ahmed Almani, Aftab; Umer, Farhana; Verdú, Elena (International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI), 06/2022)
      Machine learning-based supervised single-channel speech enhancement has achieved considerable research interest over conventional approaches. In this paper, an extended Restricted Boltzmann Machine (RBM) is proposed for ...
    • Evaluating the COVID−19 impact on tourism and access routes to Spain: a counterfactual analysis 

      Martín-Álvarez, Juan Manuel; Galiano, Aída; Martínez, Lara; Arco Osuna, Miguel Ángel del (Elsevier, 2025)
      This research examines the impact of COVID-19 on Spanish international tourism, focusing on the routes of access to the country. Using data from October 2015 to March 2024, a counterfactual analysis was conducted to calculate ...
    • Finding an accurate early forecasting model from small dataset: A case of 2019-nCoV novel coronavirus outbreak 

      Fong, Simon James; Li, Gloria; Dey, Nilanjan; González-Crespo, Rubén ; Herrera-Viedma, Enrique (International Journal of Interactive Multimedia and Artificial Intelligence, 03/2020)
      Epidemic is a rapid and wide spread of infectious disease threatening many lives and economy damages. It is important to fore-tell the epidemic lifetime so to decide on timely and remedic actions. These measures include ...
    • How Sentiment Indicators Improve Algorithmic Trading Performance 

      Gómez-Martínez, Raúl; Medrano-García, María Luisa; López-López, David; Torres-Pruñonosa, José (Sage Open, 2025)
      This study explores the hypothesis that sentiment indicators can enhance the performance of algorithmic trading strategies. Specifically, we investigate the impact of incorporating investor sentiment metrics, such as the ...
    • Hybrid Approach Based on Machine Learning for Hand Shape and Key Point's Estimation 

      Chen, Zhongshan; Feng, Xinning; Sanjuán Martínez, Óscar; González-Crespo, Rubén (Journal of Interconnection Networks, 2022)
      In human-computer interaction and virtual truth, hand pose estimation is essential. Public dataset experimental analysis Different biometric shows that a particular system creates low manual estimation errors and has a ...
    • Hybrid machine learning techniques in the management of harmful algal blooms impact 

      Molares-Ulloa, Andres; Rivero, Daniel; Gil Ruiz, Jesús; Fernandez-Blanco, Enrique; de-la-Fuente-Valentín, Luis (Computers and Electronics in Agriculture, 2023)
      Harmful algal blooms (HABs) are episodes of high concentrations of algae that are potentially toxic for human consumption. Mollusc farming can be affected by HABs because, as filter feeders, they can accumulate high ...
    • Impacto de las emociones vertidas por diarios digitales en Twitter 

      Arce García, Sergio ; Orviz Martínez, Natalia ; Cuervo Carabel, Tatiana (Profesional de la Información, 09/2020)
      The use of Twitter by newspapers is widespread and is a way to keep readers informed in real time. In this article, we analyze the discourse of the messages released by the ten main general information newspapers in Spain ...
    • Initial Approach for Construction of a Public Dataset for Emotional Analysis Through Brain-Computer Interfaces and Second Language Platforms 

      Restrepo Rodríguez, Andrés Ovidio; Ariza Riaño, Maddyzeth; Gaona-García, Paulo Alonso; Montenegro Marin, Carlos Enrique; González-Crespo, Rubén (IEEE Global Engineering Education Conference, EDUCON, 2023)
      In recent years, the deepening of the role of emotions in education has increased, since it has been shown that emotions influence what we learn and retain, in different areas such as learning a second language. Likewise, ...
    • Inteligencia artificial contra la desinformación: fundamentos, avances y retos 

      Montoro-Montarroso, Andrés; Rosso, Paolo; Panizo-Lledot, Ángel; Calvo-Figueras, Blanca; Cantón-Correa, Francisco Javier; Chulvi, Berta; Huertas-Tato, Javier; Rementeria, M. José; Gómez-Romero, Juan (Profesional de la Informacion, 2023)
      Internet y las redes sociales han revolucionado la forma en la que se distribuye y consume la información. Sin embargo, la enorme cantidad de contenidos disponibles en estas plataformas dificulta la tarea distinguir entre ...
    • Introduction to the special section on advances of machine learning in cybersecurity (VSI-mlsec) 

      Namasudra, Suyel; González-Crespo, Rubén ; Kumar, Sathish (Computers and Electrical Engineering, 2022)
      With the rapid advancement of emerging technologies, such as Internet of Things (IoT), cloud computing, and many more, a huge amount of data is generated and processed in daily life. As these technologies are based on the ...