Mostrando ítems 1-9 de 9

Data mining and social network analysis on Twitter

Silva, Jesus; Varela, Noel; Ovallos-Gazabon, David; H, H; Cazallo-Antunez, Ana; Redondo Bilbao, Osman; ORELLANO LLINAS, NATALY; Pineda Lezama, Omar Bonerge (Universidad de la Costa, 2020-03-05)

The emergence of a networked social structure in the last decade of twentieth century is accelerated by the evolution of information technologies and, in particular, the Internet has given rise to the full emergence of ...
Data mining applied in school dropout prediction

amelec, viloria; García Guliany, Jesús; Niebles Núñez, William; H, H; Niebles Nuñez, Leonardo David (Journal of Physics: Conference Series, 2020)

In recent years, many studies have emerged about regarding the topic of school failure, showing a growing interest in determining the multiple factors that may influence it [1]. Most of the researches that attempt to solve ...
Inflación venezolana: Variaciones trimestrales nominales y reales de Venezuela en el periodo 2005-2017

PITRE REDONDO, REMEDIOS CATALINA; Urdaneta Montiel, Armando José; H, H (Corporación Universidad de la Costa, 2020-01-27)

This research studied credit and Venezuelan infla-tion during the period 2005-2017. The objective was to identify nominal and real quarterly variations in Venezuela during the period 2005-2017. Methodolo-gically it was ...
Management model for the logistics and competitiveness of SMEs in the city of Barranquilla

De la Hoz Hernández, Juan David; MARTÍNEZ CARABALLO, HUGO RAMÓN; Martínez Ventura, Jairo Luis; H, H; MOJICA HERAZO, JULIO CESAR; Acosta Salgado, Sandra Milena; Rodriguez Toscano, Andres; Silva, Jesús (Universidad de la Costa, 2019)

In Colombia, small and medium-sized enterprises (SMEs) are the most powerful engines of economic development, since they generate a high volume of jobs in the national territory, while diversifying productive, commercial, ...
Measuring the financial performance of MSMEs through artificial neural network

Silva, Jesus; Hernandez, Lissette; Emilia Hernandez, Ana; Varela, Noel; H, H; Redondo Bilbao, Osman; León Castro, Nadia; Prieto Pulido, Ronald; García Guliany, Jesús (Universidad de la Costa, 2020)

Given the importance of micro, small and medium-sized enterprises (MSMEs) in Colombia, both in terms of the number of enterprises and the generation of employment, it is important to know their nature, as well as the main ...
Natural language explanation model for decision trees

Silva, Jesús; H, H; Núñez, Vladimir; Ruiz Lázaro, Alex; Varela Izquierdo, Noel (Journal of Physics: Conference Series, 2020-02-01)

This study describes a model of explanations in natural language for classification decision trees. The explanations include global aspects of the classifier and local aspects of the classification of a particular instance. ...
Neural networks for tea leaf classification

Silva, Jesús; H, H; Niebles Núñez, William; Ruiz-Lazaro, Alex; Varela, Noel (Journal of Physics: Conference Series, 2020)

The process of classification of the raw material, is one of the most important procedures in any tea dryer, being responsible for ensuring a good quality of the final product. Currently, this process in most tea processing ...
Parallel algorithm for reduction of data processing time in big data

Silva, Jesús; H, H; Niebles Núñez, William; Ovallos-Gazabon, David; Varela, Noel (Journal of Physics: Conference SeriesRetracted, 2020)

Technological advances have allowed to collect and store large volumes of data over the years. Besides, it is significant that today's applications have high performance and can analyze these large datasets effectively. ...
Time series decomposition using automatic learning techniques for predictive models

Silva, Jesús; H, H; Niebles Núñez, William; Ovallos-Gazabon, David; Varela, Noel (Journal of Physics: Conference Series, 2020)

This paper proposes an innovative way to address real cases of production prediction. This approach consists in the decomposition of original time series into time sub-series according to a group of factors in order to ...

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Data mining and social network analysis on Twitter
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Silva, Jesus | 2020-03-05

The emergence of a networked social structure in the last decade of twentieth century is accelerated by the evolution of information technologies and, in particular, the Internet has given rise to the full emergence of what has been called the Information Age [1] or the Information Society. Social media is yet another example of people’s extraordinary ability to generate, disseminate and exchange meanings in collective interpersonal communication with a massive, real-time networked system where everything tends to be connected. The analysis of the climate of opinion on Twitter is presented around the Common Core State Standards (CCSS), one of the most ambitious educational reforms of the last 50 years in USA.

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Data mining applied in school dropout prediction
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amelec, viloria | 2020

In recent years, many studies have emerged about regarding the topic of school failure, showing a growing interest in determining the multiple factors that may influence it [1]. Most of the researches that attempt to solve this issue [2] are focused on determining the factors that most affect the performance of students (dropout and failure) at the different educational levels (basic, middle and higher education) through the use of the large amount of information that current computer equipment allows to store in databases. All these data constitute a real gold mine of valuable information about students. But, identifying and finding useful and hidden information in large databases is a difficult task [3]. A very promising solution to achieve this goal is the use of knowledge mining techniques or data mining in education, which has resulted in so-called Educational Data Mining (EDM) [4]. This new area of research is concerned with the development of methods for exploring data in education, as well as the use of these methods to better understand students and the contexts where they learn [5].

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Inflación venezolana: Variaciones trimestrales nominales y reales de Venezuela en el periodo 2005-2017
...
PITRE REDONDO, REMEDIOS CATALINA | 2020-01-27

This research studied credit and Venezuelan infla-tion during the period 2005-2017. The objective was to identify nominal and real quarterly variations in Venezuela during the period 2005-2017. Methodolo-gically it was based on quantitative research, being this a correlational study, in which the data was taken from the statistical information reports pro-vided by the Central Bank of Venezuela in 2017 and SUDEBAN in 2017. The results allowed us to observe the behavior of nominal and real quarterly variations in Venezuela, allowing us to consider the great relevance that inflationary processes have in the dynamics of nations both locally and internatio-nally. Highlighting how in the financial indexes of the Venezuelan nation in the official data there is a contradiction with the current reality.

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Management model for the logistics and competitiveness of SMEs in the city of Barranquilla
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De la Hoz Hernández, Juan David | 2019

In Colombia, small and medium-sized enterprises (SMEs) are the most powerful engines of economic development, since they generate a high volume of jobs in the national territory, while diversifying productive, commercial, and service activities. In order to propose a model for logistics management as a component for the competitiveness of SMEs, a qualitative study is proposed that will allow us to collect from a structured review of recent literature, identifying the elements to be taken into account for logistics management in order to provide timely support and open space for continuous improvement. The proposed model is structured in six main blocks: characterization of processes according to the activity of the SME, external factors of influence, internal factors of influence, feeding of information, monitoring and control of operations, and feedback between support areas. The above elements have been analyzed and suggested taking into account the specific aspects of SMEs in the country, and taking into account the peculiarities of these small productive cells.

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Measuring the financial performance of MSMEs through artificial neural network
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Silva, Jesus | 2020

Given the importance of micro, small and medium-sized enterprises (MSMEs) in Colombia, both in terms of the number of enterprises and the generation of employment, it is important to know their nature, as well as the main determinantsoftheirﬁnancialperformance.Inthissense,thispaperaimsto provide relevant information for the formulation of strategies, programs and public policies that promote practices within companies and thus improve the performance of this segment of organizations.

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Natural language explanation model for decision trees
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Silva, Jesús | 2020-02-01

This study describes a model of explanations in natural language for classification decision trees. The explanations include global aspects of the classifier and local aspects of the classification of a particular instance. The proposal is implemented in the ExpliClas open source Web service [1], which in its current version operates on trees built with Weka and data sets with numerical attributes. The feasibility of the proposal is illustrated with two example cases, where the detailed explanation of the respective classification trees is shown.

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Neural networks for tea leaf classification
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Silva, Jesús | 2020

The process of classification of the raw material, is one of the most important procedures in any tea dryer, being responsible for ensuring a good quality of the final product. Currently, this process in most tea processing companies is usually handled by an expert, who performs the work manually and at his own discretion, which has a number of associated drawbacks. In this work, a solution is proposed that includes the planting, design, development and testing of a prototype that is able to correctly classify photographs corresponding to samples of raw material arrived at a dryer, using intelligence techniques (IA) type supervised for Classification by Artificial Neural Networks and not supervised with K-means Grouping for class preparation. The prototype performed well and is a reliable tool for classifying the raw material slammed into tea dryers.

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Parallel algorithm for reduction of data processing time in big data
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Silva, Jesús | 2020

Technological advances have allowed to collect and store large volumes of data over the years. Besides, it is significant that today's applications have high performance and can analyze these large datasets effectively. Today, it remains a challenge for data mining to make its algorithms and applications equally efficient in the need of increasing data size and dimensionality [1]. To achieve this goal, many applications rely on parallelism, because it is an area that allows the reduction of cost depending on the execution time of the algorithms because it takes advantage of the characteristics of current computer architectures to run several processes concurrently [2]. This paper proposes a parallel version of the FuzzyPred algorithm based on the amount of data that can be processed within each of the processing threads, synchronously and independently.

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Time series decomposition using automatic learning techniques for predictive models
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Silva, Jesús | 2020

This paper proposes an innovative way to address real cases of production prediction. This approach consists in the decomposition of original time series into time sub-series according to a group of factors in order to generate a predictive model from the partial predictive models of the sub-series. The adjustment of the models is carried out by means of a set of statistic techniques and Automatic Learning. This method was compared to an intuitive method consisting of a direct prediction of time series. The results show that this approach achieves better predictive performance than the direct way, so applying a decomposition method is more appropriate for this problem than non-decomposition. The agricultural sector will be used as the study subject.

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Listar por autor "H, H"

Data mining and social network analysis on Twitter ﻿

Data mining applied in school dropout prediction ﻿

Inflación venezolana: Variaciones trimestrales nominales y reales de Venezuela en el periodo 2005-2017 ﻿

Management model for the logistics and competitiveness of SMEs in the city of Barranquilla ﻿

Measuring the financial performance of MSMEs through artificial neural network ﻿

Natural language explanation model for decision trees ﻿

Neural networks for tea leaf classification ﻿

Parallel algorithm for reduction of data processing time in big data ﻿

Time series decomposition using automatic learning techniques for predictive models ﻿

Envíos recientes

Data mining and social network analysis on Twitter

Data mining applied in school dropout prediction

Inflación venezolana: Variaciones trimestrales nominales y reales de Venezuela en el periodo 2005-2017

Management model for the logistics and competitiveness of SMEs in the city of Barranquilla

Measuring the financial performance of MSMEs through artificial neural network

Natural language explanation model for decision trees

Neural networks for tea leaf classification

Parallel algorithm for reduction of data processing time in big data

Time series decomposition using automatic learning techniques for predictive models

Data mining and social network analysis on Twitter

Data mining applied in school dropout prediction

Inflación venezolana: Variaciones trimestrales nominales y reales de Venezuela en el periodo 2005-2017

Management model for the logistics and competitiveness of SMEs in the city of Barranquilla

Measuring the financial performance of MSMEs through artificial neural network

Natural language explanation model for decision trees

Neural networks for tea leaf classification

Parallel algorithm for reduction of data processing time in big data

Time series decomposition using automatic learning techniques for predictive models