CHI '95 Conference Companion on Human Factors in Computing Systems
Aesthetics and apparent usability: empirically assessing cultural and methodological issues
Proceedings of the ACM SIGCHI Conference on Human factors in computing systems
Personalized hypermedia and international privacy
Communications of the ACM - The Adaptive Web
Adaptive interfaces and agents
The human-computer interaction handbook
Usable adaptive hypermedia systems
Hypermedia - Special issue: Adaptive hypermedia in the age of the adaptive web
STyLE-OLM: Interactive Open Learner Modelling
International Journal of Artificial Intelligence in Education - "Caring for the Learner" in honour of John Self
Semantic Assistants --- User-Centric Natural Language Processing Services for Desktop Clients
ASWC '08 Proceedings of the 3rd Asian Semantic Web Conference on The Semantic Web
VlUM: a web-based visualisation of large user models
UM'03 Proceedings of the 9th international conference on User modeling
IntrospectiveViews: an interface for scrutinizing semantic user models
UMAP'10 Proceedings of the 18th international conference on User Modeling, Adaptation, and Personalization
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Personalization nowadays is a commodity in a broad spectrum of computer systems. Examples range from online shops recommending products identified based on the user's previous purchases to web search engines sorting search hits based on the user browsing history. The aim of such adaptive behavior is to help users to find relevant content easier and faster. However, there are a number of negative aspects of this behavior. Adaptive systems have been criticized for violating the usability principles of direct manipulation systems, namely controllability, predictability, transparency, and unobtrusiveness. In this paper, we propose an approach to controlling adaptive behavior in recommender systems. It allows users to get an overview of personalization effects, view the user profile that is used for personalization, and adjust the profile and personalization effects to their needs and preferences. We present this approach using an example of a personalized portal for biochemical literature, whose users are biochemists, biologists and genomicists. Also, we report on a user study evaluating the impacts of controllable personalization on the usefulness, usability, user satisfaction, transparency, and trustworthiness of personalized systems.