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Título
OCI-CBR: A hybrid model for decision support in preference-aware investment scenarios
Autor(es)
Palabras clave
Case-base reasoning
Capital investment
Recommender systems
Hybrid models
Machine learning
Ahorro e inversión
Aprendizaje automático
Clasificación UNESCO
1203.17 Informática
3304 Tecnología de Los Ordenadores
Fecha de publicación
2023
Editor
Elsevier
Citación
Pérez-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.
Resumen
[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.
URI
ISSN
0957-4174
DOI
10.1016/j.eswa.2022.118568
Versión del editor
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Patrocinador
Publicación en abierto financiada por la Universidad de Salamanca como participante en el Acuerdo Transformativo CRUE-CSIC con Elsevier, 2021-2024













