María Matilde García Lorenzo

María Matilde García Lorenzo
Universidad Central "Marta Abreu" de las Villas · Informatics Research Center

PhD

About

149
Publications
21,844
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Introduction
María Matilde García Lorenzo currently works at the Informatics Research Center, Universidad Central "Marta Abreu" de las Villas. María does research in Artificial Neural Network and Artificial Intelligence, Machine Learning. Their current project is 'Interpretable semi-supervised classifier'.
Additional affiliations
January 1988 - present
Universidad Central "Marta Abreu" de las Villas
Position
  • Professor
January 1986 - present
Universidad Central "Marta Abreu" de las Villas
Position
  • Professor

Publications

Publications (149)
Article
Full-text available
Introducción: La minería de opinión resulta de gran interés y utilidad para la sociedad y sectores importantes de la economía. Los textos de las opiniones son datos complejos caracterizados por complicadas relaciones semánticas y sintácticas del idioma, lo que implica un desafío a considerar desde el punto de vista computacional para la toma de dec...
Article
Imbalanced data are popular in the machine learning community due to their likelihood of appearing in real-world application areas and the problems they present for classical classifiers. The goal of this work is to extend the capabilities of prototype-based classifiers using fuzzy similarity relations and to make them sensitive to class-imbalanced...
Article
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Introducción: Los Sistemas de Información Geográfica (SIG) han adquirido gran relevancia, al aumentar el valor de la información geográfica para tomar decisiones. Mejorar la eficacia del procesamiento y la recuperación de información en SIG, teniendo en cuenta los grandes volúmenes de datos geográficos disponibles, su heterogeneidad, y la ausencia...
Article
Full-text available
Introducción. Los Sistemas de Información Geográfica (SIG) han adquirido gran relevancia, al aumentar el valor de la información geográfica para tomar decisiones. Mejorar la eficacia del procesamiento y la recuperación de información en SIG, teniendo en cuenta los grandes volúmenes de datos geográficos disponibles, su heterogeneidad, y la ausencia...
Chapter
Health is an extremely important aspect in the United Nations Sustainable Development Goals because there is not possible progress for humankind without it. The Covid19 pandemic has evidenced to what extent society can be affected in all its facets when suddenly a phenomenon affects human's health. In this chapter, it is analyzed how computational...
Article
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The use of the Internet and digital platforms to express opinions about services and products is constantly growing, constituting a source of feedback for companies. In the tourism industry, customer satisfaction is paramount, so work is being done to improve problems that may affect the quality of its services. The analysis of comments made by use...
Chapter
In recent years Fuzzy Cognitive Maps had become an important tool for expert knowledge representation due to the flexibility and interpretability of modeled maps. Its construction frequently requires an expert’s intervention but, there are situations when only the data is available or is required to extract the contained implicit knowledge for anal...
Article
COVID-19 has been affected worldwide since the end of 2019. Clinical studies have shown that a factor that increases its lethality is the existence of secondary infections. Coinfections associated with the infection SARS-CoV-2 are classified into bacterial infections and fungal infections. A patient may develop one, both, or neither. From a machine...
Article
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In supervised pattern classification, it often happens that a single individual classifier is not able to meet the requirements of the problem. This is the main reason that leads to the successful use of systems composed of several classifiers (classifier ensembles) looking to obtain better results than a single classifier. The selection of the cla...
Article
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Information quality and organizational transparency are relevant issues for corporate governance and sustainability of companies, as they contribute to reducing information asymmetry, decreasing risks, and improving the conduct of decision-makers, ensuring an ethical standard of organizational control. This work uses the COBIT framework of IT gover...
Chapter
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The General Data Protection Regulation (GDPR) addresses the protection of personal data through several principles and influences countries to improve their standards and practices. In this period of viral pandemic with significant increase of home-office activities the concern is to maintain adequate processes that increase the guarantees of compl...
Article
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La pandemia global de la COVID-19 ha afectado a todo el mundo en el año 2020. Cuba no ha escapado de este azote, a pesar de que las afectaciones han sido notablemente menores con respecto a otros países, debido a la gran prioridad que le ha puesto el país a este tema. A tono con el esfuerzo de toda la ciencia mundial para enfrentar esta pandemia, l...
Article
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Introducción. La difusión de la COVID-19 en el mundo ha provocado una avalancha de investigaciones para enfrentarla y atenuar sus efectos, a lo cual han contribuido los estudios de inteligencia artificial. Objetivos. En este trabajo se muestra cómo pueden aplicarse técnicas de inteligencia artificial, en particular de ciencias de datos y aprendizaj...
Article
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El análisis de escenario desarrolla un proceso sistemático para crear un con-junto de dos a cinco narrativas posibles que describen potenciales evoluciones de áreas clave en condiciones de incertidumbre, frecuentemente acompañados de gráficos. Ayuda a explorar un rango de posibles y plausibles futuros. El contenido del escenario está basado en vari...
Conference Paper
Semi-supervised classifiers combine labeled and unlabeled data during the learning phase in order to increase classifier's generalization capability. However, most successful semi-supervised classifiers involve complex ensemble structures and iterative algorithms which make it difficult to explain the outcome, thus behaving like black boxes. Furthe...
Preprint
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In the context of some machine learning applications, obtaining data instances is a relatively easy process but labeling them could become quite expensive or tedious. Such scenarios lead to datasets with few labeled instances and a larger number of unlabeled ones. Semi-supervised classification techniques combine labeled and unlabeled data during t...
Article
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The energy is important for the economic development of nations; and one of the main challenges today. The Electrical Union develops two systems for the automatization of transmission and distribution process: The Integral System of Network Management (SlGERE) and the Integral Management System of the Electrical Industry Construction Enterprise (SI...
Article
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In recent years, surprising amounts of news, messages, and reviews of products and services are generated in the online social media. Several efforts are being dedicated to detecting topics, as well as mining opinions in these unstructured texts. There are several approaches that compute opinion polarity, and some of them consider topics for their...
Article
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In scenarios where capturing and efficiently managing data from heterogeneous data sources can be an advantage, the development and use of ontologies is increasingly common. In this paper, an ontology-based data management model applied to the Geographic Information System denominated SIGOBE as part of the Business Management System of the Cuban El...
Article
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Information quality supported by suitable technology processes assures the organizational transparency, reduces asymmetry, cuts down risks, improves the demeanour of decision-makers and assures an ethical standard of organizational control. These technology processes can be assessed in different ways: for example, with frameworks such as ISO, risk,...
Article
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Un riesgo operativo es un riesgo de negocio principalmente en empresas que actúan en el sector financiero. Este tipo de riesgo puede ser tratado con diferentes marcos regulatorios, los específicos de riesgo, los de seguridad y los de evaluación de procesos tecnológicos como COBIT del Instituto de Gobernanza de TI. Identificar y tratar el riesgo no...
Article
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Electric companies need effective methods to visualize information. The Electric Union in Cuba works on the development of a Geographic Information System (GIS) with a conceptual basis that responds to the different user requests. For this, the research objective is to develop a model for the management of geospatial data, with the use of artificia...
Chapter
The Electrical Union in Cuba develops the Business Management System of the Electrical Union (SIGE) that focuses on the automation of electrical processes. The geographic information systems (SIGOBE) developed don’t meet the specific requirements for their generalization due to their limited updating facilities and the small spectrum they cover. Th...
Chapter
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Multi-label classification refers to the problem of associating an object with multiple labels. This problem has been successfully addressed from the perspective of problem transformation and adaptation of algorithms. Multi-Label k-Nearest Neighbour (MLkNN) is a lazy learner that has reported excellent results, still there is room for improvements....
Article
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Case-based Systems are an Artificial Intelligence paradigm widely used for the construction of intelligent decision support systems. However, there are still limitations related to the knowledge base organization and the treatment of numerical and non-numerical values that affect the effectiveness of the responses in this type of system. This resea...
Conference Paper
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Semi-supervised classification refers to a type of pattern classification problem involving both labeled and unlabeled data, where the number of labeled instances is often smaller when compared with the unlabeled ones. Although there exist several semi-supervised classifiers with high performance in different tasks, most of them are complex models...
Chapter
The team selection issue is important in the management of human resources, in which the purpose is to conduct a personnel selection process to form teams according to certain preferences. This selection problem is usually solved by ranking the candidates based on the preferences of decision-makers and allowing the decision-makers to select a candi...
Article
Full-text available
Los Sistemas Basados en Casos constituyen un paradigma de la Inteligencia Artificial ampliamente utilizado para la construcción de sistemas inteligentes de apoyo a la toma de decisiones. Sin embargo, persisten limitaciones relacionadas fundamentalmente con la organización de la base de conocimientos y el tratamiento de los valores numéricos y no nu...
Article
The amount of scientific information available on the Internet, corporate intranets, and other media is growing rapidly. Managing knowledge from the information that can be found in scientific publications is essential for any researcher. The management of scientific information is increasingly more complex and challenging, since documents collecti...
Article
The machine learning methods have been used successfully in the calculation of parameters of various problems of engineering, in which the complicated variables have a relation nonlinear among themselves and the modelation does not enable representing the intervening problem through a mathematical function of easy deduction. For the estimation of s...
Conference Paper
Full-text available
The exome or genome based high throughput screening techniques are becoming a definitive criterion in the conventional clinical analysis of the genetic diseases. However, pathogenic classification of an identified variant, is still a manual and time consuming process for clinical geneticists. Thus, to facilitate the variant classification process,...
Chapter
The information is increasing in hospital centers due to the widespread use of Electronical Medical Records, which make it necessary to develop new methods capable of processing information and ensuring its productive use. In this paper is proposed a framework of case-based reasoning for systems of clinical decision making by using the complete lin...
Article
The formation of teams in the context of personnel selection processes is relevant to the performance of organizations. The selection process is usually done using an order of preference defined by the decision maker. When two decision makers must choose from the same set of candidates, a conflict of interests that affects the result of selection a...
Conference Paper
Full-text available
Semi-supervised Classification (SSC) is becoming an attractive research filed due to the emergence of real-world problems on which the number of unlabeled examples exceeds the labeled ones. The natural complexity of this kind of problems rices up when designing algorithms with some interpretability features. In order to overcome this challenge, a n...
Article
Full-text available
To achieve an effective geographic information system, which responds to the different requests of users, a model to manage data on a deep domain conceptual scheme is needed. Based on the study of the state of the art of geographic information systems, especially those used in the electrical sector, it’s determined as the objective of this research...
Article
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Data clustering has become one of the key forms of knowledge management. Particularly knowledge management from the scientific literature available on the internet is very importance for researchers, that why, specialized techniques have been developed in scientific articles clustering. The scientific publications follow a well-defined structure wh...
Article
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In recent years the development of multi-classifier systems has become an active area research. A multi-classifier system is a set of classification algorithms whose individual outputs are fused for greater accuracy and interpretability. Many theoretical and empirical studies have shown the advantages of paradigm combination of classifiers over ind...
Article
Full-text available
In recent years, the development of multi-classifier systems has become an active research field. A multi-classifier system is an ensemble of classification algorithms whose individual outputs are fused together for better accuracy and interpretability. An important aspect when designing such systems is related to the heterogeneity of the building...
Article
Full-text available
The amount of any kind of stored data is going in an exponential increment. That is why it is needed to create efficient procedures to manipulate this data and extract knowledge from them. Data mining is in charge of this type of process and to make their procedures less complex. Methodologies have been designed to guide them. As these methodologie...
Article
Full-text available
Para el sector eléctrico se desarrolla un Sistema de Información Geográfica denominado SIGOBE versión 3.0. Las bases de datos que tributan información alfanumérica son el Sistema Integral de Gestión de la ECIE (SIGECIE) y el Sistema Integral de Gestión de Redes (SIGERE). Estudios realizados determinan la necesidad de un modelo para el manejo de dat...
Conference Paper
Full-text available
The exome or genome based high throughput screening techniques are becoming a definitive criterion in the conventional clinical analysis of the genetic diseases. However, pathogenic classification of an identified variant, is still a manual and time consuming process for clinical geneticists. Thus, to facilitate the variant classification process,...
Conference Paper
Full-text available
In this paper, we propose a novel and in-terpretable grey-box ensemble using a self-labeled approach for semi-supervised classification problems. The prospective grey-box ensembles a more interpretable white-box model with a black-box technique. This scheme could guide the comparatively data expensive white-box component with the results from the m...
Article
The personnel selection problem is a classical decision making problem. It refers to the process of choosing candidates who match, possibly to some degree, the qualifications required to perform a certain job. Personnel selection is an important activity for organizations and usually the outcome of a personnel selection method is an overall ranking...
Article
Every day more electronic data in semistructured format, specifically XML, are available on the World Wide Web, intranets, and other media. By this, the information management becomes increasingly complex and challenging, especially since document collections are generally heterogeneous, large, diverse and dynamic. Overcoming these challenges is es...
Article
Full-text available
The team selection is an important task in the management of human resources, in which the purpose is to carry out a personnel selection process in order to form teams. This process is usually performed from rankings of candidates that reflect the decision-makers’ preferences. In this work, the process of team selection is developed in a different...
Article
Full-text available
Due to the exponential increase of stored information the organizations, the information society is being overtaken by the need for new methods capable of processing information and ensuring its productive use. This is logically extended to the hospitals, from the widespread use of clinical histories in electronic format. To have systematized infor...
Conference Paper
Full-text available
El Sistema de Información Geográfica (SIG) de la Unión Eléctrica necesita generar consultas inteligentes en tiempo real. Para ello se desarrolla un Sistema Basado en Casos que involucra: tipos de datos conjuntos, ontologías y cadenas. La información se obtiene de consultas previamente realizadas al SIG que mejoran la calidad y los tiempos de respue...
Conference Paper
Full-text available
En los últimos años el ahorro de energía eléctrica se ha convertido en una de las principales tareas del país. Desde el punto de vista social, la energía es un factor importante en el desarrollo de las fuerzas productivas y en la elevación del nivel de vida de la población. Como parte del proceso de informatización, la empresa de tecnología de la i...
Article
Full-text available
This article presents a knowledge-based system for the diagnosis of cardiovascular diseases in newborns. This system is an interpretive case- based system in which an artificial neural net is combined with a case recovery module. The created model has shown better results than other traditional prognosis methods in this kind of application.
Conference Paper
Full-text available
A recent survey showed that studies concerning Fuzzy Cognitive Maps have been increased. Such knowledge-based networks are suitable for handling complex systems where neurons/concepts denote variables, entities, states or objects associated to the system under investigation. This technique is a powerful modeling tool but have the disadvantage that...
Article
Full-text available
Every day more digital data in semi-structured format are available on the World Wide Web, corporate intranets, and other media. Knowledge management using information search and processing is essential in the field of academic writing. This task becomes increasingly complex and defiant, mainly because collections of documents are usually heterogen...
Article
In this paper was presented a study of existing works on the subject of Face Expression Recognition, specifically in the sub problem of features selection for the classification. The line of studies of P. Ekman was approached as one of the most accepted and developed, as well as some alternative proposals. Both positive contributions and main drawb...
Article
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The treatment of wastewater from a factory is of vital importance, since it eliminates some of the contamination of the same ones, and thus contributes to the protection of the environment. It is necessary to bring to different companies in the territory, province and country, the experience gained in these treatments by the specialists of the Virt...
Article
Supervised classification is one of the most active research fields in the Artificial Intelligence community. Nearest Neighbor (NN) is one of the simplest and most consistently accurate approaches to supervised classification. The training set preprocessing is essential for obtaining high quality classification results. This paper introduces an att...
Article
Full-text available
Supervised classification is one of the most active research fields in the Artificial Intelligence community. Nearest Neighbor (NN) is one of the simplest and most consistently accurate approaches to supervised classification. The training set preprocessing is essential for obtaining high quality classification results. This paper introduces an att...
Article
Full-text available
This paper presents a novel algorithm for ortholog detection that involves the aggregation of similarity measures characterizing the relationship between gene pairs of two genomes. The measures are based on the alignment score, the length of the sequences, the membership in the conserved regions as well as on the protein physicochemical profile. Th...
Article
Rough sets were presented by Professor Zdzislaw Pawlak in a seminal paper published in 1982. Rough Sets Theory (RST) has evolved into a methodology for dealing with different types of problems, such as the uncertainty produced by inconsistencies in data. RST is the best tool for modeling uncertainty when it shows up as inconsistency, according to s...
Conference Paper
Learning in datasets that suffer from imbalanced class distribution is an important problem in Pattern Recognition. This paper introduces a novel algorithm for data balancing, based on compact set clustering of the majority class. The proposed algorithm is able to deal with mixed, as well as incomplete data, and with arbitrarily dissimilarity funct...
Conference Paper
Full-text available
Several antiviral drugs have been approved for treating HIV infected patients. These drugs inhibit the function of proteins which are essential in the virus life cycle, thus preventing the virus reproduction. However, due to its high mutation rate the HIV is capable to develop resistance to administered therapy. For this reason, it is important to...
Article
Full-text available
Case-based reduction is viewed as an important prepro-cessing step for case based decision-making. In this pa-per, is introduced a Support Rough Set model to deal with mixed and incomplete data. The Support Rough Set mod-el is used to reduce the case base by using positive and limit regions of decision. The proposed algorithms are compared with som...
Article
There are several classification problems, which are difficult to solve using a single classifier because of the complexity of the decision boundary. Whereas a wide variety of multiple classifier systems have been built with the purpose of improving the recognition process, there is no universal method performing the best. This paper provides a rev...
Article
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Cuban Schools for children with Affective textendash Behavioral Maladies (SABM) have as goal to accomplish a major change in children behavior, to insert them effectively into society. One of the key elements in this objective is to give an adequate orientation to the childrentextquoterights families; due to the family is one of the most important...
Article
Full-text available
Artificial Neural Networks (ANNs) are grouped within connectionist techniques of Artificial Intelligence. In particular, Recurrent Neural Networks are a type of ANN which is widely used in signal reproduction tasks and sequence analysis, where causal relationships in time and space take place. On the other hand, in many problems of science and engi...
Article
Full-text available
Artificial Neural Networks (ANNs) are grouped within connectionist techniques of Artificial Intelligence. In particular, Recurrent Neural Networks are a type of ANN which is widely used in signal reproduction tasks and sequence analysis, where causal relationships in time and space take place. On the other hand, in many problems of science and engi...
Conference Paper
Feature and instance selection before classification is a very important task, which can lead to big improvements in both classifier accuracy and classifier speed. However, few papers consider the simultaneous or combined instance and feature selection for Nearest Neighbor classifiers in a deterministic way. This paper proposes a novel deterministi...
Article
Intelligent Tutorials Systems have demonstrated their effectiveness in various applications of the teaching-learning processes. However; its construction involves a complex and intense work of knowledge engineering, which prevents a more general use and optimal use. In this work provides a model that integrates the knowledge-based systems, the Conc...
Conference Paper
The family orientation process in Cuban Schools for children with Affective – Behavioral Maladies (SABM) involves clustering and classification of mixed type data with non-symmetric similarity functions. To improve this process, this paper includes some novel characteristics in clustering and prototype selection. The proposed approach uses a hierar...
Conference Paper
In this paper, we propose a generalization of classical Rough Sets, the Nearest Neighborhood Rough Sets, by modifying the indiscernible relation without using any similarity threshold. We also combine these Rough Sets with Compact Sets, to obtain a prototype selection algorithm for Nearest Prototype Classification of mixed and incomplete data as we...
Chapter
In this article, the problem of function approximation is studied using the paradigm of the nearest prototypes. A method is proposed to construct prototypes using similarity relations; the relations are constructed using the measurement quality of similarity and the metaheuristic UMDA. For every class of similarity, a prototype is constructed. The...
Article
Full-text available
More and more often Information Technologies occupy new areas of knowledge, and the pathological diagnosis of buildings is not an exception. In this work, we offer to construction professionals and particularly those who specialize in the topic of pathological diagnosis, an expert system that uses Artificial Intelligence (AI) and a knowledge-based...
Conference Paper
The nearest neighbor rule (NN) is one of the most powerful yet simple non parametric classification techniques. However, it is time consuming and it is very sensitive to noisy as well as outlier objects. To solve these deficiencies several prototype selection methods have been proposed by the scientific community. In this paper, we propose a new ed...
Article
Full-text available
There are several classification problems in Bioinformatics which are difficult to solve using artificial intelligence techniques because of the diversity of patterns in datasets. In this paper, an ensemble of classifiers is developed to improve the accuracy of classification in bioinformatics datasets. This model is based on the use of different m...
Article
There are several classification problems in Bioinformatics which are difficult to solve using artificial intelligence techniques because of the diversity of patterns in datasets. In this paper, an ensemble of classifiers is developed to improve the accuracy of classification in bioinformatics datasets. This model is based on the use of different m...
Conference Paper
Transport “management and behavior” modeling takes place in developed societies because of the benefit that it brings for all social and economic processes. Using in this field, advanced computer science techniques like Artificial Intelligence is really relevant from the scientific, economic and social point of view. This paper deals with Fuzzy Cog...