Abstract
Web personalization has demonstrated to be advantageous for both online customers and vendors. However, current personalization methods require considerable amounts of data about users, and the benefits of personalization are therefore counteracted by privacy concerns. Personalized systems need to take these concerns into account, as well as privacy laws and industry self-regulation that may be in effect. Privacy-Enhanced Personalization aims at reconciling the goals and methods of user modeling and personalization with privacy considerations, and to strive for best possible personalization within the boundaries set by privacy. This talk surveys recent research on factors that affect people’s personal information disclosure and on personalization methods that bear fewer privacy risks, and presents design recommendations based thereon.
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© 2007 Springer-Verlag Berlin Heidelberg
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Kobsa, A. (2007). Trustbus’07 Keynote Talk Privacy Enhanced Personalization. In: Lambrinoudakis, C., Pernul, G., Tjoa, A.M. (eds) Trust, Privacy and Security in Digital Business. TrustBus 2007. Lecture Notes in Computer Science, vol 4657. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74409-2_1
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DOI: https://doi.org/10.1007/978-3-540-74409-2_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74408-5
Online ISBN: 978-3-540-74409-2
eBook Packages: Computer ScienceComputer Science (R0)