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dc.contributor.authorChamoso Santos, Pablo 
dc.contributor.authorGonzález Briones, Alfonso 
dc.contributor.authorRivas Camacho, Alberto 
dc.contributor.authorPrieta Pintado, Fernando de la 
dc.contributor.authorCorchado Rodríguez, Juan Manuel 
dc.date.accessioned2025-01-29T18:40:22Z
dc.date.available2025-01-29T18:40:22Z
dc.date.issued2019-01-03
dc.identifier.citationChamoso, P., González-Briones, A., Rivas, A. et al. Social computing in currency exchange. Knowl Inf Syst 61, 733–753 (2019). https://doi.org/10.1007/s10115-018-1289-4es_ES
dc.identifier.issn0219-1377
dc.identifier.issn0219-3116
dc.identifier.urihttp://hdl.handle.net/10366/163136
dc.description.abstract[EN]Human communication has evolved over the last decades thanks to rapid technological advances. It has provided us with new ways of communicating with one another and made many aspects of social interaction easier. Social computing is an important area in computer science concerned with the use of computational systems for social purposes. This paper focuses on the use of social computing to simplify the process of currency exchange at airports where services have to be provided to people of all nationalities. This is a complex social scenario in which the buyer and seller must reach an agreement without speaking the same language, and in these cases, the probability of not understanding all the aspects of the transaction is high. The proposed system improves interaction between users and ensures a fast and secure operation. A multi-agent system is the base of the developed software; MAS is an important and commonly used tool in social computing. A case study was conducted with the proposed system at Sydney airport, with a Spanish currency exchange company (Global Exchange) which provides service to travelers from all continents. The Net Promoter Score metric was used to evaluate the developed system, and a score of 29.81 was obtained, indicating that customers were highly satisfied with the performance of the system. Moreover, thanks to the system, there was an increase of 34% in currency exchange operations, and the time it takes to provide service to a customer reduced by 73.67% on average.es_ES
dc.language.isoenges_ES
dc.publisherSpringer Naturees_ES
dc.subjectCurrency exchangees_ES
dc.subjectSocial computinges_ES
dc.subjectSoftwarees_ES
dc.subjectMulti-agent systemses_ES
dc.titleSocial computing in currency exchangees_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publishversionhttps://doi.org/10.1007/s10115-018-1289-4es_ES
dc.identifier.doi10.1007/s10115-018-1289-4
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.journal.titleKnowledge and Information Systemses_ES
dc.volume.number61es_ES
dc.issue.number2019es_ES
dc.page.initial733es_ES
dc.page.final753es_ES
dc.type.hasVersioninfo:eu-repo/semantics/submittedVersiones_ES


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