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dc.contributor.authorPérez-Pons, María-Eugenia
dc.contributor.authorParra Domínguez, Javier 
dc.contributor.authorHernández González, Guillermo 
dc.contributor.authorBichindaritz, Isabelle
dc.contributor.authorCorchado Rodríguez, Juan Manuel 
dc.date.accessioned2024-11-29T12:54:09Z
dc.date.available2024-11-29T12:54:09Z
dc.date.issued2023
dc.identifier.citationPérez-Pons, M. E., Parra-Dominguez, J., Hernández, G., Bichindaritz, I., & Corchado, J. M. (2023). OCI-CBR: A hybrid model for decision support in preference-aware investment scenarios. Expert Systems with Applications, 211, 118568.es_ES
dc.identifier.issn0957-4174
dc.identifier.issn1873-6793
dc.identifier.urihttp://hdl.handle.net/10366/160845
dc.description.abstract[EN] This article proposes an adaptable hybrid model for recommending effective investments in different scenarios. Currently, a wide variety of methodologies are used for company valuation, especially those that take into account financial statements. However, for private held companies, there is no method that would be capable of predicting, with full certainty, the future success of an investment. The Optimal Capital Investment Case-Base Reasoning (OCI-CBR) consists of a case-based reasoning system that uses a classification algorithm to prune the case base according to a projected increase in certain company attributes. Once the cases have been pruned and the case is fed with the most profitable investment opportunities, the case-based reasoning system recommends optimal investments to potential investors. The complete model is conceived as an intelligent hybrid model that optimizes the case base by employing different algorithms for data retrieval and reuse. The system makes recommendations based on the investor’s preferences and the investment decisions of other investors with similar profiles or interests.es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectCase-base reasoninges_ES
dc.subjectCapital investmentes_ES
dc.subjectRecommender systemses_ES
dc.subjectHybrid modelses_ES
dc.subjectMachine learninges_ES
dc.subjectAhorro e inversiónes_ES
dc.subjectAprendizaje automáticoes_ES
dc.titleOCI-CBR: A hybrid model for decision support in preference-aware investment scenarioses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publishversionhttps://doi.org/10.1016/j.eswa.2022.118568es_ES
dc.subject.unesco1203.17 Informáticaes_ES
dc.subject.unesco3304 Tecnología de Los Ordenadoreses_ES
dc.identifier.doi10.1016/j.eswa.2022.118568
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.journal.titleExpert Systems with Applicationses_ES
dc.volume.number211es_ES
dc.page.initial118568es_ES
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones_ES
dc.description.projectPublicación en abierto financiada por la Universidad de Salamanca como participante en el Acuerdo Transformativo CRUE-CSIC con Elsevier, 2021-2024es_ES


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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Excepto si se señala otra cosa, la licencia del ítem se describe como Attribution-NonCommercial-NoDerivatives 4.0 Internacional