AH '08 Proceedings of the 5th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems
Performance Evaluation of a Privacy-Enhancing Framework for Personalized Websites
UMAP '09 Proceedings of the 17th International Conference on User Modeling, Adaptation, and Personalization: formerly UM and AH
A PLA-based privacy-enhancing user modeling framework and its evaluation
User Modeling and User-Adapted Interaction
Personalized recommender systems integrating tags and item taxonomy
Web Intelligence and Agent Systems
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Adaptive Web systems utilize user models (or group models) to represent essential information about an individual user (or a group) so that these systems can adapt their behavior to the goals, tasks, interests, and other features of individual users or groups of users. Meanwhile, proper performance assessment has become a critical issue for the efficient deployment of adaptive Web systems that implement complex user model inferences. This paper presents one of the first efforts to develop a framework for evaluating the performance of user modeling servers (UMS). We conduct a performance-driven analysis of the UMS conceptual model, extracting a comprehensive set of parameters in order to build a practical UMS Performance Evaluation Framework (UMS/PEF). We also apply the proposed UMS/PEF framework for comparing performances between different UMS. Experimental results have demonstrated high utility of the proposed UMS/PEF framework. This work was partially supported by NSF CRCD/EI Award 0426021 and NSF CAREER Award 0447083.