Abstract
The problem of preserving privacy in recommendation systems is faced in this work. The approach presented reduces the study of privacy threats to the study of frequent property set obtained from the characteristics of the objects the recommendation system provides to a target user. This study is made by defining a prominence index for each item and by using efficient methods to explore the lattice of item characteristics.
Author acknowledges financial support by Grant TEC2012-38142-C04-04 from Ministry of Education and Science, Government of Spain and by Grant UNOV-13-EMERG-GIJON-10 from University of Oviedo, Spain.
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Troiano, L., Díaz, I. (2014). A Model for Preserving Privacy in Recommendation Systems. In: Laurent, A., Strauss, O., Bouchon-Meunier, B., Yager, R.R. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2014. Communications in Computer and Information Science, vol 443. Springer, Cham. https://doi.org/10.1007/978-3-319-08855-6_7
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DOI: https://doi.org/10.1007/978-3-319-08855-6_7
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