Abstract
We present a study comparing collaborative filtering methods enhanced with user personality traits and cross-domain ratings in multiple domains on a relatively large dataset. We show that incorporating additional ratings from source domains allows improving the accuracy of recommendations in a different target domain, and that in certain cases, it is better to enrich user models with both cross-domain ratings and personality trait information.
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Fernández-Tobías, I., Cantador, I. (2015). On the Use of Cross-Domain User Preferences and Personality Traits in Collaborative Filtering. In: Ricci, F., Bontcheva, K., Conlan, O., Lawless, S. (eds) User Modeling, Adaptation and Personalization. UMAP 2015. Lecture Notes in Computer Science(), vol 9146. Springer, Cham. https://doi.org/10.1007/978-3-319-20267-9_29
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DOI: https://doi.org/10.1007/978-3-319-20267-9_29
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