Respecting users' individual privacy constraints in web personalization

Yang Wang, Alfred Kobsa

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


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
Number of pages10
ISBN (Print)9783540730774
StatePublished - Dec 24 2007
Externally publishedYes
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


Conference11th International User Modeling Conference, UM 2007

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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