Jose Olivas | University of Castilla-La Mancha (original) (raw)

Papers by Jose Olivas

Communications in computer and information science, 2018

The purpose of this paper is to show that it is possible to describe stress levels through a comp... more The purpose of this paper is to show that it is possible to describe stress levels through a complete time-log analysis. For this purpose it has been developed a fuzzy deformable prototypes based model that uses a fuzzy representation of the prototypical situations. The proposed model has been applied to a database composed of time logs from students with and without stress. Preliminary results from the proposed model application have been validated by experts. Moreover, the model has been applied as a classifier obtaining good results for both sensitivity and specificity. Finally, the proposal has been validated and should be considered useful for the expert systems design to support the stress level description.

Abstract—Due to the Internet, new ways to access to and manage health care information are contin... more Abstract—Due to the Internet, new ways to access to and manage health care information are continuously appearing. All of them allow that data stores can grow with more and more data, which has not always the adequate levels of quality. Manage such amount of data ...

Springer eBooks, Oct 29, 2007

Cognitive psychology works have shown that the cognitive representation of categories is based on... more Cognitive psychology works have shown that the cognitive representation of categories is based on a typicality notion: all objects of a category do not have the same representativeness, some are more characteristic or more typical than others, and better exemplify their category. Categories are then defined in terms of prototypes, i.e. in terms of their most typical elements. Furthermore, these works showed that an object is all the more typical of its category as it shares many features with the other members of the category and few features with the members of other categories. In this paper, we propose to profit from these principles in a machine learning framework: a formalization of the previous cognitive notions is presented, leading to a prototype building method that makes it possible to characterize data sets taking into account both common and discriminative features. Algorithms exploiting these prototypes to perform tasks such as classification or clustering are then presented. The formalization is based on the computation of typicality degrees that measure the representativeness of each data point. These typicality degrees are then exploited to define fuzzy prototypes: in adequacy with human-like description of categories, we consider a prototype as an intrinsically imprecise notion. The fuzzy logic framework makes it possible to model sets with unsharp boundaries or vague and approximate concepts, and appears most appropriate to model prototypes. We then exploit the computed typicality degrees and the built fuzzy prototypes to perform machine learning tasks such as classification and clustering. We present several algorithms, justifying in each case the chosen parameters. We illustrate the results obtained on several data sets corresponding both to crisp and fuzzy data.

Applied Soft Computing, Dec 1, 2020

Online reviews have a significant impact on the decisions of consumers, providing valuable inform... more Online reviews have a significant impact on the decisions of consumers, providing valuable information which must be managed from two different perspectives: that of the user who reads the review and the people who gave those opinions. These two perspectives are the basis of the novel fuzzy aspectbased sentiment analysis approach described in this paper to recommend the most suitable products for a specific user. This approach consists of a T1OWA-based mechanism to characterize the user profile, which is able to model whether the user can be more influenced by negative opinions or positive opinions, a mechanism for determining their preferences, and a variation coefficient method for weighting the importance of the aspects of the product reviews. Combining these ideas, our model outperforms other well-known methods for ranking products, while also having the advantage of being adaptable to the preferences and characteristics of a specific user.

Intelligent Data Analysis, Dec 4, 2020

Automatic keyphrase extraction from texts is useful for many computational systems in the fields ... more Automatic keyphrase extraction from texts is useful for many computational systems in the fields of natural language processing and text mining. Although a number of solutions to this problem have been described, semantic analysis is one of the least exploited linguistic features in the most widely-known proposals, causing the results obtained to have low accuracy and performance rates. This paper presents an unsupervised method for keyphrase extraction, based on the use of lexico-syntactic patterns for extracting information from texts, and a fuzzy topic modeling. An OWA operator combining several semantic measures was applied to the topic modeling process. This new approach was evaluated with Inspec and 500N-KPCrowd datasets. Several approaches within our proposal were evaluated against each other. A statistical analysis was performed to substantiate the best approach of the proposal. This best approach was also compared with other reported systems, giving promising results.

Procesamiento Del Lenguaje Natural, Sep 1, 2018

En este trabajo se presenta una primera aproximación de un modelo de recuperación de información ... more En este trabajo se presenta una primera aproximación de un modelo de recuperación de información personalizada basado en el procesamiento semántico del contenido. El modelo propuesto reduce la sobrecarga de información innecesaria para los usuarios y mejora los resultados recuperados mediante la combinación de un procesamiento semántico de contenido aplicado a las consultas y documentos indexados, y la información de los perfiles de usuarios. La aplicabilidad de la propuesta fue evaluada en el contexto de un motor de búsqueda real, a través de consultas diseñadas por expertos en diferentes dominios y la medición de su rendimiento. Los resultados obtenidos fueron comparados con los del motor de búsqueda puesto a prueba, lográndose mejoras en cuanto a la precisión y exhaustividad.

Artificial Intelligence in Medicine, Jun 1, 2022

International Journal of Intelligent Systems, Aug 27, 2021

The process to assess a hospital performance usually needs the interaction of a lot of experts an... more The process to assess a hospital performance usually needs the interaction of a lot of experts and patients and is very costly and time‐consuming. Nevertheless, the availability of patient opinions on the Internet offers a great opportunity to develop systems that evaluate hospitals based on user feedback. The content of these opinions is very challenging, including information about the hospital services but also stories about their own patients, their families, and personal feelings or beliefs before or after leaving a hospital. Therefore, the task of recommending hospitals according to the quality of their services becomes really complicated. This study describes an application for ranking hospitals based on the user preferences about the different offered services as well as the opinions about them. First, it semiautomatically classifies all predefined hospital aspects, calculates the sentiment orientation, and represents their associated polarity by intuitionistic fuzzy sets. Second, by means of the user preferences towards the different aspects, an aggregation operator, and a multicriteria decision‐making algorithm, all hospitals are ranked. To assess this methodology, a large set of reviews about hospitals have been collected. Further, considering all patient ratings about the different hospitals, an algorithm for ranking them is proposed, which develops baselines for comparison. In addition, an interval‐valued Pythagorean fuzzy approach has been also implemented to compare the obtained results. These results confirm the soundness of the proposal.

Nowadays, the impact of e-Learning developments on improving educational activities is becoming m... more Nowadays, the impact of e-Learning developments on improving educational activities is becoming more evident. The Portfolio approach has emerged as important alternative to increase the learning process. However, most of tools to support portfolio assessment are far from to come up to the expectations. In this work we propose a fuzzy ontology-based framework to support portfolio assessment. Our approach focuses on portfolio semantic representation and conceptual matching to generate a portfolio evaluation report, which helps teachers in portfolio assessment tasks. The initial experiments results indicate that the approach is useful and warrants further research.

Procesamiento Del Lenguaje Natural, Sep 5, 2017

La extracción automática de frases relevantes constituye una tarea de gran importancia para mucha... more La extracción automática de frases relevantes constituye una tarea de gran importancia para muchas soluciones computacionales en el área del procesamiento de lenguaje natural y la minería de texto. En este trabajo se propone un nuevo método no supervisado para la extracción de frases relevantes en textos, en el cual se combina el uso de patrones léxico-sintácticos con una estrategia de análisis de tópicos basada en grafo. El método fue evaluado con los corpus SemEval-2010 e INSPEC y comparado con otras propuestas del estado del arte, obteniéndose resultados muy prometedores. Palabras claves: Extracción automática de frases relevantes, minería de texto, procesamiento de lenguaje natural

IEEE International Conference on Cloud Computing Technology and Science, 2021

Communications in computer and information science, 2018

For the ideal functioning of an intelligent tutoring system it is essential to be able to estimat... more For the ideal functioning of an intelligent tutoring system it is essential to be able to estimate the level of skill of the students according to complex learning objectives. We propose an architecture for the evaluation of the student’s skill level, based on the multi-attribute utility theory, using as aggregation operator the Choquet integral. The method takes into account the learning objectives raised by the decision maker (academics, school teachers, heads of institutions, etc.) represented by complex relationships that can be found among the criteria considered for the evaluation.

2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2017

Inliers and Outliers are widely studied in the world of databases. In the early 80's, L. A. Z... more Inliers and Outliers are widely studied in the world of databases. In the early 80's, L. A. Zadeh proposed an interesting approach to the concept of ‘prototype’ which contrasts with the classical theories of prototypes from the field of cognitive psychology. This definition has not been used much in fuzzy scientific proposals. Metasearch engines are often designed and used for Information Retrieval tasks because they are cheap and easy to develop, as they get their results from multiple search engines. In this paper, a definition of Inliers and Outliers is presented and related to Zadeh's concept of fuzzy prototype: Inliers with the prototype of the borderline elements and Outliers with the prototype of the bad elements of a dataset. Then, this approach is used for dealing with the User Profiles in a real Scientific Metasearcher with the aim of proposing recommendations, sending warnings and in general enriching the management of these User Profiles. An example and experiments proposal in this real system are also presented.

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2019

The automatic keyphrases extraction from texts is a useful task for many computational systems in... more The automatic keyphrases extraction from texts is a useful task for many computational systems in the natural language processing and text mining fields. Although several solutions to this problem have been developed, the semantic analysis has been one of the linguistic features less exploited in the most reported proposal, causing that the obtained results still show low accuracy and performance rates. This paper presents an unsupervised method for keyphrase extraction, which is based on the use of lexical-syntactic patterns for extracting information from texts and a fuzzy modelling of topics. An OWA operator which combines several semantics measures has been applied in the topic modelling process. This new approach was evaluated with Inspec and 500N-KPCrowd datasets and compared with other reported systems, obtaining promising results.

Proces. del Leng. Natural, 2019

espanolLa generacion automatica de resumenes consiste en sintetizar en un texto corto la informac... more espanolLa generacion automatica de resumenes consiste en sintetizar en un texto corto la informacion mas relevante contenida en documentos, y permite reducir los problemas generados por la sobrecarga de informacion. En este trabajo se presenta un metodo no supervisado de generacion de resumenes extractivos a partir de multiples documentos. En esta propuesta, la conceptualizacion y estructura semantica subyacente del contenido textual se representa en un grafo semantico usando WordNet y se aplica un algoritmo de agrupamiento de conceptos para identificar los topicos tratados en los documentos, con los cuales se evalua la relevancia de las oraciones para construir el resumen. El metodo fue evaluado con corpus de textos de MultiLing 2015, y se usaron metricas de ROUGE para medir la calidad de los resumenes generados. Los resultados obtenidos se compararon con los de otros sistemas participantes en MultiLing 2015, evidenciandose mejoras en la mayoria de los casos. | EnglishThe automatic...

Proces. del Leng. Natural, 2021

Este trabajo ha sido parcialmente financiado por el Fondo Europeo de Desarrollo Regional (FEDER),... more Este trabajo ha sido parcialmente financiado por el Fondo Europeo de Desarrollo Regional (FEDER), la Junta de Extremadura (GR18135), y el Ministerio de Ciencia, Innovacion y Universidades de Espana, a traves del proyecto SAFER (PID2019-104735RB-C42).

2020 IEEE Congreso Bienal de Argentina (ARGENCON), 2020

This article presents an overview of emotional recognition of music (MER) through the fuzzy logic... more This article presents an overview of emotional recognition of music (MER) through the fuzzy logic approach. First, related papers are reviewed to analyze how fuzzy logic is used in each phase of a typical MER process. Subsequently, a prototype of a fuzzy system is designed to classify musical pieces by arousal levels, defining the tempo of the songs as the system’s input and the level of arousal as the output. Based on the review of the literature and the results obtained with the fuzzy system prototype, a discussion is presented to improve the understanding of the main differences between classification systems with fuzzy logic or with machine learning approaches, focusing on the success rate of MER, especially in the labeling and classification processes. This review and the comparison of both approaches (fuzzy logic and machine learning) reveal fuzzy logic’s principal contributions, expand the knowledge of the current developments in MER and present possible improvements for the design of MER systems.

J. of Electrical Engineering, 2018

At present, all people know that, during the performance of any activity, each person is always u... more At present, all people know that, during the performance of any activity, each person is always under the influence of a set of external factors that can influence in their results. In fact, all people know that factors such as hour, accumulated fatigue, or mood, can be very influential in the productivity. However, there are other less studied factors that can equally be influential, to a greater or lesser extent. For this reason, in the present work are used different techniques belonging to Soft Computing, with the objective of detecting those most influential factors by the execution of a set of experiments under different simulated circumstances in a controlled environment.

Cloud Computing and Big Data, 2019

The cryptocurrencies are a new paradigm of transferring money between users. Their anonymous and ... more The cryptocurrencies are a new paradigm of transferring money between users. Their anonymous and non-centralized is a subject of debate around the globe that paired with the massive spikes and declines in value that are inherit to an unregistered asset. These facts make difficult for the common daily use of the cryptocurrencies as an exchange currency as instead they are being used as a new way to invest. What we propose in this article is a system for the better understanding of the cryptocurrencies economical behavior against the global market. For that we are using Data Analytics techniques to build a predictor that uses as inputs said external financial variable. These forecasts would help determine if a coin is safe to trade with, if those forecasts can be precise by only using this external data. The results obtained indicates us that there is a certain degree of influence of the global market to the cryptocurrencies, but that is it not enough to correctly predict the fluctuations in price of the coins and that they care more about others factors and that they have their own bubbles, like the crypto collapse in late 2017.

Communications in computer and information science, 2018

The purpose of this paper is to show that it is possible to describe stress levels through a comp... more The purpose of this paper is to show that it is possible to describe stress levels through a complete time-log analysis. For this purpose it has been developed a fuzzy deformable prototypes based model that uses a fuzzy representation of the prototypical situations. The proposed model has been applied to a database composed of time logs from students with and without stress. Preliminary results from the proposed model application have been validated by experts. Moreover, the model has been applied as a classifier obtaining good results for both sensitivity and specificity. Finally, the proposal has been validated and should be considered useful for the expert systems design to support the stress level description.

Abstract—Due to the Internet, new ways to access to and manage health care information are contin... more Abstract—Due to the Internet, new ways to access to and manage health care information are continuously appearing. All of them allow that data stores can grow with more and more data, which has not always the adequate levels of quality. Manage such amount of data ...

Springer eBooks, Oct 29, 2007

Cognitive psychology works have shown that the cognitive representation of categories is based on... more Cognitive psychology works have shown that the cognitive representation of categories is based on a typicality notion: all objects of a category do not have the same representativeness, some are more characteristic or more typical than others, and better exemplify their category. Categories are then defined in terms of prototypes, i.e. in terms of their most typical elements. Furthermore, these works showed that an object is all the more typical of its category as it shares many features with the other members of the category and few features with the members of other categories. In this paper, we propose to profit from these principles in a machine learning framework: a formalization of the previous cognitive notions is presented, leading to a prototype building method that makes it possible to characterize data sets taking into account both common and discriminative features. Algorithms exploiting these prototypes to perform tasks such as classification or clustering are then presented. The formalization is based on the computation of typicality degrees that measure the representativeness of each data point. These typicality degrees are then exploited to define fuzzy prototypes: in adequacy with human-like description of categories, we consider a prototype as an intrinsically imprecise notion. The fuzzy logic framework makes it possible to model sets with unsharp boundaries or vague and approximate concepts, and appears most appropriate to model prototypes. We then exploit the computed typicality degrees and the built fuzzy prototypes to perform machine learning tasks such as classification and clustering. We present several algorithms, justifying in each case the chosen parameters. We illustrate the results obtained on several data sets corresponding both to crisp and fuzzy data.

Applied Soft Computing, Dec 1, 2020

Online reviews have a significant impact on the decisions of consumers, providing valuable inform... more Online reviews have a significant impact on the decisions of consumers, providing valuable information which must be managed from two different perspectives: that of the user who reads the review and the people who gave those opinions. These two perspectives are the basis of the novel fuzzy aspectbased sentiment analysis approach described in this paper to recommend the most suitable products for a specific user. This approach consists of a T1OWA-based mechanism to characterize the user profile, which is able to model whether the user can be more influenced by negative opinions or positive opinions, a mechanism for determining their preferences, and a variation coefficient method for weighting the importance of the aspects of the product reviews. Combining these ideas, our model outperforms other well-known methods for ranking products, while also having the advantage of being adaptable to the preferences and characteristics of a specific user.

Intelligent Data Analysis, Dec 4, 2020

Automatic keyphrase extraction from texts is useful for many computational systems in the fields ... more Automatic keyphrase extraction from texts is useful for many computational systems in the fields of natural language processing and text mining. Although a number of solutions to this problem have been described, semantic analysis is one of the least exploited linguistic features in the most widely-known proposals, causing the results obtained to have low accuracy and performance rates. This paper presents an unsupervised method for keyphrase extraction, based on the use of lexico-syntactic patterns for extracting information from texts, and a fuzzy topic modeling. An OWA operator combining several semantic measures was applied to the topic modeling process. This new approach was evaluated with Inspec and 500N-KPCrowd datasets. Several approaches within our proposal were evaluated against each other. A statistical analysis was performed to substantiate the best approach of the proposal. This best approach was also compared with other reported systems, giving promising results.

Procesamiento Del Lenguaje Natural, Sep 1, 2018

En este trabajo se presenta una primera aproximación de un modelo de recuperación de información ... more En este trabajo se presenta una primera aproximación de un modelo de recuperación de información personalizada basado en el procesamiento semántico del contenido. El modelo propuesto reduce la sobrecarga de información innecesaria para los usuarios y mejora los resultados recuperados mediante la combinación de un procesamiento semántico de contenido aplicado a las consultas y documentos indexados, y la información de los perfiles de usuarios. La aplicabilidad de la propuesta fue evaluada en el contexto de un motor de búsqueda real, a través de consultas diseñadas por expertos en diferentes dominios y la medición de su rendimiento. Los resultados obtenidos fueron comparados con los del motor de búsqueda puesto a prueba, lográndose mejoras en cuanto a la precisión y exhaustividad.

Artificial Intelligence in Medicine, Jun 1, 2022

International Journal of Intelligent Systems, Aug 27, 2021

The process to assess a hospital performance usually needs the interaction of a lot of experts an... more The process to assess a hospital performance usually needs the interaction of a lot of experts and patients and is very costly and time‐consuming. Nevertheless, the availability of patient opinions on the Internet offers a great opportunity to develop systems that evaluate hospitals based on user feedback. The content of these opinions is very challenging, including information about the hospital services but also stories about their own patients, their families, and personal feelings or beliefs before or after leaving a hospital. Therefore, the task of recommending hospitals according to the quality of their services becomes really complicated. This study describes an application for ranking hospitals based on the user preferences about the different offered services as well as the opinions about them. First, it semiautomatically classifies all predefined hospital aspects, calculates the sentiment orientation, and represents their associated polarity by intuitionistic fuzzy sets. Second, by means of the user preferences towards the different aspects, an aggregation operator, and a multicriteria decision‐making algorithm, all hospitals are ranked. To assess this methodology, a large set of reviews about hospitals have been collected. Further, considering all patient ratings about the different hospitals, an algorithm for ranking them is proposed, which develops baselines for comparison. In addition, an interval‐valued Pythagorean fuzzy approach has been also implemented to compare the obtained results. These results confirm the soundness of the proposal.

Nowadays, the impact of e-Learning developments on improving educational activities is becoming m... more Nowadays, the impact of e-Learning developments on improving educational activities is becoming more evident. The Portfolio approach has emerged as important alternative to increase the learning process. However, most of tools to support portfolio assessment are far from to come up to the expectations. In this work we propose a fuzzy ontology-based framework to support portfolio assessment. Our approach focuses on portfolio semantic representation and conceptual matching to generate a portfolio evaluation report, which helps teachers in portfolio assessment tasks. The initial experiments results indicate that the approach is useful and warrants further research.

Procesamiento Del Lenguaje Natural, Sep 5, 2017

La extracción automática de frases relevantes constituye una tarea de gran importancia para mucha... more La extracción automática de frases relevantes constituye una tarea de gran importancia para muchas soluciones computacionales en el área del procesamiento de lenguaje natural y la minería de texto. En este trabajo se propone un nuevo método no supervisado para la extracción de frases relevantes en textos, en el cual se combina el uso de patrones léxico-sintácticos con una estrategia de análisis de tópicos basada en grafo. El método fue evaluado con los corpus SemEval-2010 e INSPEC y comparado con otras propuestas del estado del arte, obteniéndose resultados muy prometedores. Palabras claves: Extracción automática de frases relevantes, minería de texto, procesamiento de lenguaje natural

IEEE International Conference on Cloud Computing Technology and Science, 2021

Communications in computer and information science, 2018

For the ideal functioning of an intelligent tutoring system it is essential to be able to estimat... more For the ideal functioning of an intelligent tutoring system it is essential to be able to estimate the level of skill of the students according to complex learning objectives. We propose an architecture for the evaluation of the student’s skill level, based on the multi-attribute utility theory, using as aggregation operator the Choquet integral. The method takes into account the learning objectives raised by the decision maker (academics, school teachers, heads of institutions, etc.) represented by complex relationships that can be found among the criteria considered for the evaluation.

2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2017

Inliers and Outliers are widely studied in the world of databases. In the early 80's, L. A. Z... more Inliers and Outliers are widely studied in the world of databases. In the early 80's, L. A. Zadeh proposed an interesting approach to the concept of ‘prototype’ which contrasts with the classical theories of prototypes from the field of cognitive psychology. This definition has not been used much in fuzzy scientific proposals. Metasearch engines are often designed and used for Information Retrieval tasks because they are cheap and easy to develop, as they get their results from multiple search engines. In this paper, a definition of Inliers and Outliers is presented and related to Zadeh's concept of fuzzy prototype: Inliers with the prototype of the borderline elements and Outliers with the prototype of the bad elements of a dataset. Then, this approach is used for dealing with the User Profiles in a real Scientific Metasearcher with the aim of proposing recommendations, sending warnings and in general enriching the management of these User Profiles. An example and experiments proposal in this real system are also presented.

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2019

The automatic keyphrases extraction from texts is a useful task for many computational systems in... more The automatic keyphrases extraction from texts is a useful task for many computational systems in the natural language processing and text mining fields. Although several solutions to this problem have been developed, the semantic analysis has been one of the linguistic features less exploited in the most reported proposal, causing that the obtained results still show low accuracy and performance rates. This paper presents an unsupervised method for keyphrase extraction, which is based on the use of lexical-syntactic patterns for extracting information from texts and a fuzzy modelling of topics. An OWA operator which combines several semantics measures has been applied in the topic modelling process. This new approach was evaluated with Inspec and 500N-KPCrowd datasets and compared with other reported systems, obtaining promising results.

Proces. del Leng. Natural, 2019

espanolLa generacion automatica de resumenes consiste en sintetizar en un texto corto la informac... more espanolLa generacion automatica de resumenes consiste en sintetizar en un texto corto la informacion mas relevante contenida en documentos, y permite reducir los problemas generados por la sobrecarga de informacion. En este trabajo se presenta un metodo no supervisado de generacion de resumenes extractivos a partir de multiples documentos. En esta propuesta, la conceptualizacion y estructura semantica subyacente del contenido textual se representa en un grafo semantico usando WordNet y se aplica un algoritmo de agrupamiento de conceptos para identificar los topicos tratados en los documentos, con los cuales se evalua la relevancia de las oraciones para construir el resumen. El metodo fue evaluado con corpus de textos de MultiLing 2015, y se usaron metricas de ROUGE para medir la calidad de los resumenes generados. Los resultados obtenidos se compararon con los de otros sistemas participantes en MultiLing 2015, evidenciandose mejoras en la mayoria de los casos. | EnglishThe automatic...

Proces. del Leng. Natural, 2021

Este trabajo ha sido parcialmente financiado por el Fondo Europeo de Desarrollo Regional (FEDER),... more Este trabajo ha sido parcialmente financiado por el Fondo Europeo de Desarrollo Regional (FEDER), la Junta de Extremadura (GR18135), y el Ministerio de Ciencia, Innovacion y Universidades de Espana, a traves del proyecto SAFER (PID2019-104735RB-C42).

2020 IEEE Congreso Bienal de Argentina (ARGENCON), 2020

This article presents an overview of emotional recognition of music (MER) through the fuzzy logic... more This article presents an overview of emotional recognition of music (MER) through the fuzzy logic approach. First, related papers are reviewed to analyze how fuzzy logic is used in each phase of a typical MER process. Subsequently, a prototype of a fuzzy system is designed to classify musical pieces by arousal levels, defining the tempo of the songs as the system’s input and the level of arousal as the output. Based on the review of the literature and the results obtained with the fuzzy system prototype, a discussion is presented to improve the understanding of the main differences between classification systems with fuzzy logic or with machine learning approaches, focusing on the success rate of MER, especially in the labeling and classification processes. This review and the comparison of both approaches (fuzzy logic and machine learning) reveal fuzzy logic’s principal contributions, expand the knowledge of the current developments in MER and present possible improvements for the design of MER systems.

J. of Electrical Engineering, 2018

At present, all people know that, during the performance of any activity, each person is always u... more At present, all people know that, during the performance of any activity, each person is always under the influence of a set of external factors that can influence in their results. In fact, all people know that factors such as hour, accumulated fatigue, or mood, can be very influential in the productivity. However, there are other less studied factors that can equally be influential, to a greater or lesser extent. For this reason, in the present work are used different techniques belonging to Soft Computing, with the objective of detecting those most influential factors by the execution of a set of experiments under different simulated circumstances in a controlled environment.

Cloud Computing and Big Data, 2019

The cryptocurrencies are a new paradigm of transferring money between users. Their anonymous and ... more The cryptocurrencies are a new paradigm of transferring money between users. Their anonymous and non-centralized is a subject of debate around the globe that paired with the massive spikes and declines in value that are inherit to an unregistered asset. These facts make difficult for the common daily use of the cryptocurrencies as an exchange currency as instead they are being used as a new way to invest. What we propose in this article is a system for the better understanding of the cryptocurrencies economical behavior against the global market. For that we are using Data Analytics techniques to build a predictor that uses as inputs said external financial variable. These forecasts would help determine if a coin is safe to trade with, if those forecasts can be precise by only using this external data. The results obtained indicates us that there is a certain degree of influence of the global market to the cryptocurrencies, but that is it not enough to correctly predict the fluctuations in price of the coins and that they care more about others factors and that they have their own bubbles, like the crypto collapse in late 2017.