Goal-oriented Email Stream Classifier with A Multi-agent System Approach
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http://hdl.handle.net/10045/118701
Títol: | Goal-oriented Email Stream Classifier with A Multi-agent System Approach |
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Autors: | Hojas-Mazo, Wenny | Moreno-Espino, Mailyn | Berna-Martinez, Jose Vicente | Maciá Pérez, Francisco | Lorenzo Fonseca, Iren |
Grups d'investigació o GITE: | GrupoM. Redes y Middleware |
Centre, Departament o Servei: | Universidad de Alicante. Departamento de Tecnología Informática y Computación |
Paraules clau: | Email stream classification | Goal-oriented requirements | i* | Multi-agent system |
Àrees de coneixement: | Arquitectura y Tecnología de Computadores |
Data de publicació: | 2021 |
Editor: | SAI Organization |
Citació bibliogràfica: | International Journal of Advanced Computer Science and Applications (IJACSA). 2021, 12(9): 575-580. https://doi.org/10.14569/IJACSA.2021.0120965 |
Resum: | Now-a-days, email is often one of the most widely used means of communication despite the rise of other communication methods such as instant messaging or communication via social networks. The need to automate the email stream management increases for reasons such as multi-folder categorization, and spam email classification. There are solutions based on email content, capable of contemplating elements such as the text subjective nature, adverse effects of concept drift, among others. This paper presents an email stream classifier with a goal-oriented approach to client and server environment. The i* language was the basis for designing the proposed email stream classifier. The email environment was represented with the early requirements model and the proposed classifier with the late requirements model. The classifier was implemented following a multi-agent system approach supported by JADE agent platform and Implementation_JADE pattern. The behavior of agents was taking from an existing classifier. The multi-agent classifier was evaluated using functional, efficacy and performance tests, which compared the existing classifier with the multi-agent approach. The results obtained were satisfactory in all the tests. The performance of multi-agent approach was better than the existing classifier due to the use of multi-threads. |
Patrocinadors: | This work was performed as part of the Smart University Project financed by the University of Alicante. |
URI: | http://hdl.handle.net/10045/118701 |
ISSN: | 2158-107X (Print) | 2156-5570 (Online) |
DOI: | 10.14569/IJACSA.2021.0120965 |
Idioma: | eng |
Tipus: | info:eu-repo/semantics/article |
Drets: | This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited. |
Revisió científica: | si |
Versió de l'editor: | https://doi.org/10.14569/IJACSA.2021.0120965 |
Apareix a la col·lecció: | INV - GrupoM - Artículos de Revistas |
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Arxiu | Descripció | Tamany | Format | |
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Hojas-Mazo_etal_2021_IJACSA.pdf | 607,89 kB | Adobe PDF | Obrir Vista prèvia | |
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