Abstract
The main objective of this paper aims at developing a methodology that takes into account the human factor extracted from the several information sources of the organization of the recommender systems. This methodology is capable of extracting the Human Values Scale from the user, with reference to his/her features, in order to improve the adaptation of the Recommender Systems. This research is focused on the analysis of human values scale using the Portrait Values Questionnaire of Schwartz, which can take advantage of the several information sources of the organization through its attributes to define the methodology that response with more exactitude to preferences and interests of the user. This paper presents a demonstration of how the Human Values Scale of a user can be extracted from several information sources of the organization. A case study is presented to apply the methodology, in an effort to extract the user human values scale from bank domains.
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Guzmán-Obando, J., de la Rosa, J.L., Aciar, S., Montaner, M., Castán, J.A., Laria, J. (2008). The User’s Human Values Scale Methodology in Recommender Systems from Several Information Sources of the Organization. In: Gelbukh, A., Morales, E.F. (eds) MICAI 2008: Advances in Artificial Intelligence. MICAI 2008. Lecture Notes in Computer Science(), vol 5317. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88636-5_85
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DOI: https://doi.org/10.1007/978-3-540-88636-5_85
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