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Mostrando ítems 1-10 de 14
Ponencia
MOPNAR-BigData: un diseño MapReduce para la extracción de reglas de asociación cuantitativas en problemas de big data
(Asociación Española de Inteligencia Artificial, 2015-11)
El término big data se ha extendido rápidamente en el área de la minera de datos debido a que las grandes cantidades de datos que se generan hoy en da no pueden ser procesadas o analizadas por las técnicas tradicionales ...
Artículo
Benchmarking real-time vehicle data streaming models for a smart city
(Elsevier, 2017)
The information systems of smart cities offer project developers, institutions, industry and experts the possibility to handle massive incoming data from diverse information sources in order to produce new information ...
Artículo
MRQAR: A generic MapReduce framework to discover quantitative association rules in big data problems
(Elsevier, 2018)
Many algorithms have emerged to address the discovery of quantitative association rules from datasets in the last years. However, this task is becoming a challenge because the processing power of most existing techniques ...
Ponencia
CC4Spark: Distributing Event Logs and big complex Conformance Checking problems
(CEUR Workshop Proceedings (CEUR-WS.org), 2021)
Conformance checking is one of the disciplines that best exposes the power of process mining, since it allows detecting anomalies and deviations in business processes, helping to assess and improve the quality of these. ...
Artículo
External clustering validity index based on chi-squared statistical test
(Elsevier, 2019)
Clustering is one of the most commonly used techniques in data mining. Its main goal is to group objects into clusters so that each group contains objects that are more similar to each other than to objects in other ...
Artículo
Empowering conformance checking using Big Data through horizontal decomposition
(Elsevier, 2021)
Conformance checking unleashes the full power of process mining: techniques from this discipline enable the analysis of the quality of a process model through the discovery of event data, the identification of potential ...
Artículo
An approach to validity indices for clustering techniques in Big Data
(Springer, 2018)
Clustering analysis is one of the most used Machine Learning techniques to discover groups among data objects. Some clustering methods require the number of clus ters into which the data is going to be partitioned. There ...
Artículo
Coronavirus Optimization Algorithm: A Bioinspired Metaheuristic Based on the COVID-19 Propagation Model
(Mary Ann Liebert, 2020)
This study proposes a novel bioinspired metaheuristic simulating how the coronavirus spreads and infects healthy people. From a primary infected individual (patient zero), the coronavirus rapidly infects new victims, ...
Ponencia
Un Recorrido por los Principales Proveedores de Servicios de Machine Learning y Predicción en la Nube
(Sociedad de Ingeniería de Software y Tecnologías de Desarrollo de Software (SISTEDES), 2018)
Los medios tecnológicos para el consumo, producción e intercambio de información no hacen más que aumentar cada día que pasa. Nos encontramos envueltos en el fenómeno Big Data, donde ser capaces de analizar esta informa ...
Ponencia
SmartFD: A Real Big Data Application for Electrical Fraud Detection
(Springer, 2018)
The main objective of this paper is the application of big data analytics to a real case in the field of smart electric networks. Smart meters are not only elements to measure consumption, but they also con stitute a ...