Embedding Emotional Context in Recommender Systems
dc.contributor.author
dc.date.accessioned
2010-06-08T10:20:04Z
dc.date.available
2010-06-07T12:26:11Z
2010-06-08T10:20:04Z
dc.date.issued
2007
dc.identifier.citation
González, G. , Rosa, J.L. de la , Montaner, M., i Delfín, S. (2007). Embedding Emotional Context in Recommender Systems. IEEE 23rd International Conference on Data Engineering Workshop : 2007, 845-852. Recuperat 08 juny 2010, a http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4401075
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978-1-4244-0832-0
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dc.description.abstract
Emotions are crucial for user's decision making in recommendation processes. We first introduce ambient recommender systems, which arise from the analysis of new trends on the exploitation of the emotional context in the next generation of recommender systems. We then explain some results of these new trends in real-world applications through the smart prediction assistant (SPA) platform in an intelligent learning guide with more than three million users. While most approaches to recommending have focused on algorithm performance. SPA makes recommendations to users on the basis of emotional information acquired in an incremental way. This article provides a cross-disciplinary perspective to achieve this goal in such recommender systems through a SPA platform. The methodology applied in SPA is the result of a bunch of technology transfer projects for large real-world rccommender systems
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application/pdf
dc.language.iso
eng
dc.publisher
IEEE
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Reproducció digital del document publicat a: http://dx.doi.org/10.1109/ICDEW.2007.4401075
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© IEEE 23rd International Conference on Data Engineering Workshop : 2007, 2007, p. 845-852
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Articles publicats (D-EEEiA)
dc.rights
Tots els drets reservats
dc.subject
dc.title
Embedding Emotional Context in Recommender Systems
dc.type
info:eu-repo/semantics/article
dc.rights.accessRights
info:eu-repo/semantics/openAccess
dc.identifier.doi