Respecting users' individual privacy constraints in web personalization

Yang Wang, Alfred Kobsa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

24 Scopus citations

Abstract

Web personalization has demonstrated to be advantageous for both online customers and vendors. However, its benefits may be severely counteracted 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.

Original languageEnglish (US)
Title of host publicationUser Modeling 2007 - 11th International Conference, UM 2007, Proceedings
Pages157-166
Number of pages10
StatePublished - Dec 24 2007
Event11th International User Modeling Conference, UM 2007 - Corfu, Greece
Duration: Jun 25 2007Jun 29 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4511 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other11th International User Modeling Conference, UM 2007
CountryGreece
CityCorfu
Period6/25/076/29/07

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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    Wang, Y., & Kobsa, A. (2007). Respecting users' individual privacy constraints in web personalization. In User Modeling 2007 - 11th International Conference, UM 2007, Proceedings (pp. 157-166). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4511 LNCS).