The objective of this thesis project is to develop a framework that provides mechanisms to the user to balance personalization and privacy on the web. To achieve this we suggest a browser based adaptation engine that allows the user to choose what portions of her user model will be stored on the client and what will be on the server, trading privacy for personalization. Given that the server can store some data, data-driven adaptation can be enabled, therefore a way to bring together data-driven and expert-driven adaptation has to be defined. Finally it would be interesting to perform meta-adaptation to enhance this data-driven personaliization. Keywords: Adaptation, client-side modeling, data-driven adaptation, expert-driven adaptation, meta-adaptation, server-side modeling, user modeling.
|Publication status||Published - 2014|
|Event||conference; User Modeling, Adaptation and Personalization; 2014-07-07; 2014-07-11 - |
Duration: 7 Jul 2014 → 11 Jul 2014
|Conference||conference; User Modeling, Adaptation and Personalization; 2014-07-07; 2014-07-11|
|Period||7/07/14 → 11/07/14|
|Other||User Modeling, Adaptation and Personalization|
Bibliographical noteEditor(s): Cantador, I.; Chi, M.; Farzan, R.; Jäschke, R.
22nd International Conference on User Modeling, Adaptation and Personalization (UMAP 2014, Aalborg, Denmark, July 7-11, 2014)