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1
objeto de conferencia
Indexado en Scopus
2
artículo
Publicado 2019
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This article presents a methodology that applies natural language processing and classification algorithms by using data mining techniques, and incorporating procedures for validation and verification of significance. This is conducted according to the analysis and selection of data and results based on quality statistical analysis, which guarantees the effectiveness percentage in knowledge construction. The analysis of computer incidents within an educational institution and a standardized database of historical computer incidents collected by the Service Desk area is used as case study. Such area is linked to all information technology processes and focuses on the support requirements for the performance of employee activities. As long as users’ requirements are not fulfilled in a timely manner, the impact of incidents may give rise to work problems at different levels, making it d...
3
artículo
Publicado 2019
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This article presents a methodology that applies natural language processing and classification algorithms by using data mining techniques, and incorporating procedures for validation and verification of significance. This is conducted according to the analysis and selection of data and results based on quality statistical analysis, which guarantees the effectiveness percentage in knowledge construction. The analysis of computer incidents within an educational institution and a standardized database of historical computer incidents collected by the Service Desk area is used as case study. Such area is linked to all information technology processes and focuses on the support requirements for the performance of employee activities. As long as users’ requirements are not fulfilled in a timely manner, the impact of incidents may give rise to work problems at different levels, making it d...
4
tesis de grado
Publicado 2022
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Durante los últimos años se ha observado una enfermedad con mayor incidencia en niños y adolescentes, siendo esta la debilidad ósea, la cual puede ser el inicio de enfermedades óseas crónicas y futuro cáncer de huesos, es por ello que nuestro objetivo es detectar la debilidad ósea en niños, niñas y adolescentes a través de indicadores antropométricos en las zonas alto andinas del Perú, específicamente en la ciudad de Arequipa. Aplicando diversas técnicas de minería de datos que permiten un análisis profundo y la predicción que estos algoritmos indican después del entrenamiento. Se trabajó con datos de 1511 personas entre niños y adolescentes. Se utilizó la metodología Knowledge Discovery in Databases para realizar el pre-entrenamiento de datos. Al aplicar los algoritmos de clasificación se obtuvo que 2 de cada 5 personas entre niños y adolescentes padecen debilid...
5
artículo
This paper reviews the most recent literature on experiments with different Machine Learning, Deep Learning and Natural Language Processing techniques applied to predict judicial and administrative decisions. Among the most outstanding findings, we have that the most used data mining techniques are Support Vector Machine (SVM), K Nearest Neighbours (K-NN) and Random Forest (RF), and in terms of the most used deep learning techniques, we found Long-Term Memory (LSTM) and transformers such as BERT. An important finding in the papers reviewed was that the use of machine learning techniques has prevailed over those of deep learning. Regarding the place of origin of the research carried out, we found that 64% of the works belong to studies carried out in English-speaking countries, 8% in Portuguese and 28% in other languages (such as German, Chinese, Turkish, Spanish, etc.). Very few works of...
6
artículo
One mechanism for estimating software quality is through the use of metrics, which are functions that evaluates certain characteristics of the product quality development. A software product can be evaluated from different points of view, and in that sense, the results of the evaluations are numeric vectors, which together describe the quality of the software. This research uses data from NASA's open access which undergo a process of reducing the dimensionality by principal component analysis (PCA), then applied three clustering techniques and evaluates the best grouping using Rand Index. Finally, the top clusters are tested with regression to find the metrics that are related to the error of the Software. The results suggest that groups consisting of software modules whose code source have a higher average of blank lines, show a higher density of error. This could be interpreted as an i...
7
artículo
Publicado 2016
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The present work has as objective to apply data mining techniques to develop a predictive model to forecast the chance of passing that will have a college student at the time of enrolling in a particular subject. Given that the academic record of the student can be known, and based on that information, we propose an Artificial Neural Network (ANN) that allows, using various configurations, to predict and assess our goal. The model has been applied to a compulsory subject of higher education of a University and given the results obtained. This model can be applied to any other subject analogous with satisfactory results.
8
artículo
Publicado 2004
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The present article emphasizes the use of data mining for the discovery of knowledge, with the purpose of contributing in taking tactical decisions and strategies within an organization providing an automated sense to generate knowledge. Techniques, the predictive power of statistical models and the contribution of the various fields of the research have been included.
9
artículo
Publicado 2004
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The present article emphasizes the use of data mining for the discovery of knowledge, with the purpose of contributing in taking tactical decisions and strategies within an organization providing an automated sense to generate knowledge. Techniques, the predictive power of statistical models and the contribution of the various fields of the research have been included.
10
artículo
Publicado 2022
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Research shows that data analysis and artificial intelligence applied to agriculture in Peru can help manage crop production and mitigate monetary losses. This work presents SmartAgro, a system based on pattern mining and classification techniques that takes information from multiple sources related to the agricultural process to extract knowledge and produce recommendations about the crop growth process. The problem we seek to mitigate with our system is the economic losses generated in Peruvian agriculture caused by poor crop planning. Our results show a high accuracy in regards to type of crop recommendation, and a knowledge base useful for agricultural planning.
11
objeto de conferencia
Indexado en Scopus
12
artículo
Publicado 2024
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The objective of this study is to predict the quantity of ANFO required for bench blasting in an open pit mine in Peru, through the application of advanced machine learning techniques. Six models were selected: Artificial Neural Networks (ANNMLP), Random Forests (RF), Support Vector Machines for Regression (SVR), Extreme Gradient Boosting (XGBoost), K-Nearest Neighbors (KNN), and Bayesian Regression (BR), due to their ability to handle complex multidimensional data and their success in similar applications, such as rock fragmentation prediction. The methodology included the collection of data from 208 drill holes, which were divided into training (70%), validation (15%), and testing (15%) sets. The models were evaluated using RMSE, MSE, MAE, and R2. The KNN model showed the best performance, with an R2 of 0.84, RMSE of 2.37, MSE of 5.60, and MAE of 1.35, standing out in predictive accura...
13
artículo
Publicado 2018
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Academic performance is a subject that has been studied for a long time. First year students in universities are the most vulnerable to face performance problems, resulting in possible desertion. Data mining in education applies data mining techniques in the information generated in the education sector. The present research consists of making the prediction of the academic performance of the students who entered the Professional School of Computer and Systems Engineering of the University of San Martín de Porres in the first cycle using data mining. Data were extracted from 1304 entrants who were classified using three factors: social, economic and academic, and predictions were made using three techniques: linear regression, decision tree and support vector machines, having the best result of 82.87% obtained using the decision tree. Out of the different factors, those that most influe...
14
tesis de grado
Diabetes has become such a common, but deadly, chronic health problem that it has _x000D_ increased dramatically in recent years. About 50% of all people with diabetes are not _x000D_ diagnosed due to its long-term asymptomatic phase, which is why detecting diabetes in an _x000D_ early phase is of vital importance. Science has advanced so much in the field of health that _x000D_ data mining classification techniques have been well accepted by the scientific community _x000D_ for the predictive model of disease risk. In the present investigation, a set of 520 data has _x000D_ been used, which information was collected through a direct survey of patients from the _x000D_ Sylhet Diabetes Hospital in Bangladesh. The respective analysis was carried out using _x000D_ classification algorithms such as Logistic Regression (classical statistical technique) and _x000D_ Support Vector Machine (mach...
15
artículo
Publicado 2024
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Nowadays, implementing data analytics is necessary to improve the collection, evaluation, analysis, and organization of data that allow the discovery of patterns, correlations, and trends that improve knowledge management, development of strategies, and decision-making in the organization. Therefore, this study aims to provide an accurate and detailed assessment of the current state of data analytics in the retail sector, identifying specific areas of improvement to strengthen knowledge management in organizations. The research is applied with a quantitative approach and non-experimental design at a descriptive and propositional level. The survey technique was used, and as a data collection instrument, a questionnaire addressed to 351 employees of companies in the retail sector concerning the variable data analysis with the dimensions of data extraction, predictive analysis, and machine ...
16
capítulo de libro
Publicado 2019
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This work proposes a semi-automated analysis and modeling package for Machine Learning related problems. The library goal is to reduce the steps involved in a traditional data science roadmap. To do so, Sparkmach takes advantage of Machine Learning techniques to build base models for both classification and regression problems. These models include exploratory data analysis, data preprocessing, feature engineering and modeling. The project has its basis in Pymach, a similar library that faces those steps for small and medium-sized datasets (about ten millions of rows and a few columns). Sparkmach central labor is to scale Pymach to overcome big datasets by using Apache Spark distributed computing, a distributed engine for large-scale data processing, that tackle several data science related problems in a cluster environment. Despite the software nature, Sparkmach can be of use for local ...
17
tesis de grado
Publicado 2021
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Lately the level of competition between companies in the light automotive industry is reaching a very high level, due to the various strategies developed by many competitors. Our study seeks to strengthen the evaluation of forecasts to improve the organization's capability to anticipate future events in important business processes, such as sales and maintenance services. To achieve this objective, investigations related to Data Mining techniques were consulted, in order to perform an information analysis with a predictive approach. Our research involves designing different models applying methods such as regressions, neural networks and decision trees, to a historical database of an automotive organization, previously selecting data using techniques such as the correlation matrix and PCA (Principal Component Analysis). Finally, an evaluation is carried out on the results obtained after ...
18
artículo
Publicado 2019
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Earth's behavior comprehension can be achieved by the analysis of Remote Sensing data, but considering the unprecedented volumes of information currently provided by different satellites sensors, the problem can be regarded as a big data problem. Machine learning techniques have the potential to improve the analysis of this type of data; however, most current machine learning algorithms are unable to properly process such huge volumes of data. In the attempt to overcome the computational limitations related to Remote Sensing Big Data analysis, we implemented the K-Means algorithms, a clustering technique, as distributed solution, exploiting the capabilities of cloud computing infrastructure for processing very large datasets. The solution was developed over the InterCloud Data Mining Package, which is a suite of distributed classification methods, previously employed in hyperspectral ima...
19
informe técnico
Publicado 2001
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The study area covers the Central Andean region of the Republic of Peru where a lot of skarn type metallic ore deposit such as Huanzala zinc-lead deposit, Pallca zinc.lead deposit and Anta Mina copper-zinc deposit occurs. This study aims evaluate the applicability of ASTER data for the determination of the geologic settings forming a skarn type ore deposit. Regional analysis using LANDSAT TM data was consequently executed and new promising areas for metallic ore deposit are selected out. The study was carried out with the collaboration of Instituto Geológico Minero y Metalúrgico del Perú “INGEMMET”. The study clarified that the spectral analysis using ASTER data was effective to detect the geologic settings forming skarn type ore deposit when the surface mineral indication is remarkable such as in Anta Mina deposit and Pallca deposit. Mineral mapping using ASTER data did not alway...
20
artículo
Matrix of guidelines to improve the understandability of non-expert users in process mining projects
Publicado 2020
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El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.
