Recent Submissions

  • Predicciones financieras basadas en análisis de sentimiento de textos y minería de opiniones 

    Arratia Quesada, Argimiro Alejandro (FUNCAS, 2021-04-01)
    Part of book or chapter of book
    Restricted access - publisher's policy
    En este capítulo se describe la mecánica básica para construir un modelo de predicción que utiliza indicadores de sentimiento derivados de datos textuales. Enfocamos nuestro objetivo de predicciones en series de ...
  • Sentiment analysis of financial news: mechanics and statistics 

    Arratia Quesada, Argimiro Alejandro; Ávalos Villaseñor, Gustavo Eduardo; Cabaña Nigro, Ana Alejandra; Duarte López, Ariel; Renedo Mirambell, Martí (Springer, 2021-06-11)
    Part of book or chapter of book
    Open Access
    This chapter describes the basic mechanics for building a forecasting model that uses as input sentiment indicators derived from textual data. In addition, as we focus our target of predictions on financial time series, ...
  • A fuzzy rule model for high level musical features on automated composition systems 

    Paz Ortiz, Iván; Nebot Castells, M. Àngela; Múgica Álvarez, Francisco; Romero Merino, Enrique (Springer, 2017)
    Part of book or chapter of book
    Open Access
    Algorithmic composition systems are now well-understood. However, when they are used for specific tasks like creating material for a part of a piece, it is common to prefer, from all of its possible outputs, those exhibiting ...
  • A weighted Cramer's V index for the assessment of stability in the fuzzy clustering of class C G protein-coupled receptors 

    Vellido Alcacena, Alfredo; Halka, Christiana; Nebot Castells, M. Àngela (Springer, 2015)
    Part of book or chapter of book
    Open Access
    After decades of intensive use, K-Means is still a common choice for crisp data clustering in real-world applications, particularly in biomedicine and bioinformatics. It is well-known that different initializations of the ...
  • Social aggravation estimation to seismic hazard using classical fuzzy methods 

    González Cárdenas, Rubén; Nebot Castells, M. Àngela; Múgica Álvarez, Francisco; Carreño Tibaduiza, Martha Liliana; Barbat Barbat, Horia Alejandro (Springer, 2015)
    Part of book or chapter of book
    Open Access
    In the last years, from a disasters perspective, risk has been dimensioned to allow a better management. However, this conceptualization turns out to be limited or constrained, by the generalized use of a fragmented risk ...
  • Using the Fuzzy Inductive Reasoning methodology to improve coherence in algorithmic musical beat patterns 

    Paz Ortiz, Alejandro Iván; Nebot Castells, M. Àngela; Múgica Álvarez, Francisco; Romero Merino, Enrique (IOS Press, 2014-10-23)
    Part of book or chapter of book
    Open Access
    In the present work, the Fuzzy Inductive Reasoning methodology (FIR) is used to improve coherence among beat patterns, structured in a musical A-B form. Patterns were generated based on a probability matrix, encoding a ...
  • Fuzzy models: Easier to understand and an easier way to handle uncertainties in climate change research 

    Gay García, Carlos; Sánchez Meneses, Oscar; Martínez-López, Benjamín; Nebot Castells, M. Àngela; Estrada, Francisco (2014)
    Part of book or chapter of book
    Restricted access - publisher's policy
    Greenhouse gas emission scenarios (through 2100) developed by the Intergovernmental Panel on Climate Change when converted to concentrations and atmospheric temperatures through the use of climate models result in a wide ...
  • Small-particle pollution modeling using fuzzy approaches 

    Nebot Castells, M. Àngela; Múgica Álvarez, Francisco (2014)
    Part of book or chapter of book
    Restricted access - publisher's policy
    Air pollution caused by small particles is a major public health problem in many cities of the world. One of the most contaminated cities is Mexico City. The fact that it is located in a volcanic crater surrounded by ...
  • Feature selection for the prediction and visualization of brain tumor types using proton magnetic resonance spectroscopy data 

    González Navarro, Félix Fernando; Belanche Muñoz, Luis Antonio (Springer, 2012)
    Part of book or chapter of book
    Restricted access - publisher's policy
    In cancer diagnosis, classification of the different tumor types is of great importance. An accurate prediction of basic tumor types provides better treatment and may minimize the negative impact of incorrectly targeted ...
  • Parsimonious selection of useful genes in microarray gene expression data 

    González Navarro, Félix Fernando; Belanche Muñoz, Luis Antonio (Springer, 2011)
    Part of book or chapter of book
    Open Access
    Machine Learning methods have of late made significant efforts to solving multidisciplinary problems in the field of cancer classification in microarray gene expression data. These tasks are characterized by a large number ...
  • Intelligent management of sepsis in the intensive care unit 

    Ribas Ripoll, Vicent; Ruiz Rodríguez, Juan Carlos; Vellido Alcacena, Alfredo (IGI Global, 2012-06)
    Part of book or chapter of book
    Restricted access - publisher's policy
  • On the use of graphical models to study ICU outcome prediction in septic patients treated with statins 

    Ribas, Vicent J.; Caballero López, Jesús; Sáez de Tejada, Anna; Ruiz Rodríguez, Juan Carlos; Ruiz Sanmartin, Adolfo; Rello, Jordi; Vellido Alcacena, Alfredo (Springer, 2012)
    Part of book or chapter of book
    Restricted access - publisher's policy

View more