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Evolutionary Multi-objective Scheduling for Anti-Spam Filtering Throughput Optimization

datacite.subject.sdg08:Trabalho Digno e Crescimento Económico
datacite.subject.sdg09:Indústria, Inovação e Infraestruturas
datacite.subject.sdg10:Reduzir as Desigualdades
dc.contributor.authorRuano-Ordás, David
dc.contributor.authorBasto-Fernandes, Vitor
dc.contributor.authorYevseyeva, Iryna
dc.contributor.authorMéndez, José Ramón
dc.date.accessioned2025-11-26T16:02:04Z
dc.date.available2025-11-26T16:02:04Z
dc.date.issued2017-06-21
dc.description.abstractThis paper presents an evolutionary multi-objective optimization problem formulation for the anti-spam filtering problem, addressing both the classification quality criteria (False Positive and False Negative error rates) and email messages classification time (minimization). This approach is compared to single objective problem formulations found in the literature, and its advantages for decision support and flexible/adaptive anti-spam filtering configuration is demonstrated. A study is performed using the Wirebrush4SPAM framework anti-spam filtering and the SpamAssassin email dataset. The NSGA-II evolutionary multi-objective optimization algorithm was applied for the purpose of validating and demonstrating the adoption of this novel approach to the anti-spam filtering optimization problem, formulated from the multi-objective optimization perspective. The results obtained from the experiments demonstrated that this optimization strategy allows the decision maker (anti-spam filtering system administrator) to select among a set of optimal and flexible filter configuration alternatives with respect to classification quality and classification efficiency.eng
dc.description.sponsorshipSING group thanks CITI (Centro de Investigación, Transferencia e Innovación) from University of Vigo for hosting its IT infrastructure Funding: This work was partially funded by Consellería de Cultura, Educación e Ordenación Universitaria (Xunta de Galicia) and FEDER (European Union). This work was partially supported by the project Platform of integration of intelligent techniques for analysis of biomedical information (TIN2013-47153-C3-3-R) from the Spanish Ministry of Economy and Competitiveness
dc.identifier.doi10.1007/978-3-319-59650-1_12
dc.identifier.issn0302-9743
dc.identifier.issn1611-3349
dc.identifier.urihttp://hdl.handle.net/10400.8/14744
dc.language.isoeng
dc.peerreviewedyes
dc.publisherElsevier
dc.relationTIN2013-47153-C3-3-R
dc.relation.hasversionhttps://www.scopus.com/pages/publications/85021698097?inward=
dc.relation.ispartofLecture Notes in Computer Science
dc.relation.ispartofHybrid Artificial Intelligent Systems
dc.rights.uriN/A
dc.subjectRule-based anti-spam systems
dc.subjectscheduling
dc.subjectmulti-objective optimization
dc.titleEvolutionary Multi-objective Scheduling for Anti-Spam Filtering Throughput Optimizationeng
dc.typeconference paper
dspace.entity.typePublication
oaire.citation.conferenceDate2017-06-21
oaire.citation.conferencePlaceHAIS
oaire.citation.endPage138
oaire.citation.startPage137
oaire.citation.title12th International Conference on Hybrid Artificial Intelligent Systems
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameBasto-Fernandes
person.givenNameVitor
person.identifier.ciencia-id581C-52BB-AC4E
person.identifier.orcid0000-0003-4269-5114
person.identifier.ridN-1891-2016
person.identifier.scopus-author-id53363129900
relation.isAuthorOfPublicationfb2d3703-9d6a-4c22-bbc4-9ff14c162feb
relation.isAuthorOfPublication.latestForDiscoveryfb2d3703-9d6a-4c22-bbc4-9ff14c162feb

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