%0 Journal Article %1 keyhere %A Kobsa, Alfred %D 2007 %J The Adaptive Web %K recommender-systems %P 628--670 %T Privacy-Enhanced Web Personalization %U http://dx.doi.org/10.1007/978-3-540-72079-9_21 %X Consumer studies demonstrate that online users value personalized content. At the same time, providing personalization on websites seems quite profitable for web vendors. This win-win situation is however marred by privacy concerns since personalizingpeople’s interaction entails gathering considerable amounts of data about them. As numerous recent surveys have consistentlydemonstrated, computer users are very concerned about their privacy on the Internet. More over, the collection of personaldata is also subject to legal regulations in many countries and states. Both user concerns and privacy regulations impactfrequently used personalization methods. This article analyzes the tension between personal ization and privacy, and presentsapproaches to reconcile the both.

@article{keyhere, abstract = {Consumer studies demonstrate that online users value personalized content. At the same time, providing personalization on websites seems quite profitable for web vendors. This win-win situation is however marred by privacy concerns since personalizingpeople’s interaction entails gathering considerable amounts of data about them. As numerous recent surveys have consistentlydemonstrated, computer users are very concerned about their privacy on the Internet. More over, the collection of personaldata is also subject to legal regulations in many countries and states. Both user concerns and privacy regulations impactfrequently used personalization methods. This article analyzes the tension between personal ization and privacy, and presentsapproaches to reconcile the both.}, added-at = {2009-04-10T12:21:54.000+0200}, author = {Kobsa, Alfred}, biburl = {https://www.bibsonomy.org/bibtex/24401b8978fc4bb0fbdd5eb05abd3a944/claudio.lucchese}, description = {SpringerLink - Book Chapter}, interhash = {e81484755647a71b6d9a75a40e3bbaf7}, intrahash = {4401b8978fc4bb0fbdd5eb05abd3a944}, journal = {The Adaptive Web}, keywords = {recommender-systems}, pages = {628--670}, timestamp = {2009-04-10T12:21:54.000+0200}, title = {Privacy-Enhanced Web Personalization}, url = {http://dx.doi.org/10.1007/978-3-540-72079-9_21}, year = 2007 }