Framework Based on Simulation of Real-World Message Streams to Evaluate Classification Solutions
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Título: | Framework Based on Simulation of Real-World Message Streams to Evaluate Classification Solutions |
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Autor/es: | Hojas-Mazo, Wenny | Maciá Pérez, Francisco | Berna-Martinez, Jose Vicente | Moreno-Espino, Mailyn | Lorenzo Fonseca, Iren | Pavón Mestras, Juan |
Grupo/s de investigación o GITE: | GrupoM. Redes y Middleware |
Centro, Departamento o Servicio: | Universidad de Alicante. Departamento de Tecnología Informática y Computación |
Palabras clave: | Classification | Evaluation | Non-stationary message streams | Simulation |
Fecha de publicación: | 21-ene-2024 |
Editor: | MDPI |
Cita bibliográfica: | Hojas-Mazo W, Maciá-Pérez F, Berná Martínez JV, Moreno-Espino M, Lorenzo Fonseca I, Pavón J. Framework Based on Simulation of Real-World Message Streams to Evaluate Classification Solutions. Algorithms. 2024; 17(1):47. https://doi.org/10.3390/a17010047 |
Resumen: | Analysing message streams in a dynamic environment is challenging. Various methods and metrics are used to evaluate message classification solutions, but often fail to realistically simulate the actual environment. As a result, the evaluation can produce overly optimistic results, rendering current solution evaluations inadequate for real-world environments. This paper proposes a framework based on the simulation of real-world message streams to evaluate classification solutions. The framework consists of four modules: message stream simulation, processing, classification and evaluation. The simulation module uses techniques and queueing theory to replicate a real-world message stream. The processing module refines the input messages for optimal classification. The classification module categorises the generated message stream using existing solutions. The evaluation module evaluates the performance of the classification solutions by measuring accuracy, precision and recall. The framework can model different behaviours from different sources, such as different spammers with different attack strategies, press media or social network sources. Each profile generates a message stream that is combined into the main stream for greater realism. A spam detection case study is developed that demonstrates the implementation of the proposed framework and identifies latency and message body obfuscation as critical classification quality parameters. |
URI: | http://hdl.handle.net/10045/140059 |
ISSN: | 1999-4893 |
DOI: | 10.3390/a17010047 |
Idioma: | eng |
Tipo: | info:eu-repo/semantics/article |
Derechos: | © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
Revisión científica: | si |
Versión del editor: | https://doi.org/10.3390/a17010047 |
Aparece en las colecciones: | INV - GrupoM - Artículos de Revistas |
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Hojas-Mazo_etal_2024_Algorithms.pdf | 437,69 kB | Adobe PDF | Abrir Vista previa | |
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