Abstract
Web personalization has demonstrated to be advantageous for both online customers and vendors. However, its benefits may be severely counter acted by privacy constraints. Personalized systems need to take users’ privacy concerns into account, as well as privacy laws and industry self-regulation that may be in effect. In this paper, we first discuss how these constraints may affect web-based personalized systems. We then explain in what way current approaches to this problem fall short of their aims, specifically regarding the need to tailor privacy to the constraints of each individual user. We present a dynamic privacy-enhancing user modeling framework as a superior alternative, which is based on a software product line architecture. Our system dynamically selects personalization methods during runtime that respect users’ current privacy concerns as well as the privacy laws and regulations that apply to them.
This research has been supported through NSF grant IIS 0308277. We would like to thank André van der Hoek, Eric Dashofy and the UM07 reviewers for their helpful comments.
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Wang, Y., Kobsa, A. (2007). Respecting Users’ Individual Privacy Constraints in Web Personalization . In: Conati, C., McCoy, K., Paliouras, G. (eds) User Modeling 2007. UM 2007. Lecture Notes in Computer Science(), vol 4511. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73078-1_19
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DOI: https://doi.org/10.1007/978-3-540-73078-1_19
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