Exponentiated gradient versus gradient descent for linear predictors
Information and Computation
An algorithmic framework for performing collaborative filtering
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
The role of adaptive hypermedia in a context-aware tourist GUIDE
Communications of the ACM - The Adaptive Web
Hybrid Recommender Systems: Survey and Experiments
User Modeling and User-Adapted Interaction
Ontology-Based User Modeling in an Augmented Audio Reality System for Museums
User Modeling and User-Adapted Interaction
User Modeling and User-Adapted Interaction
Adaptive, intelligent presentation of information for the museum visitor in PEACH
User Modeling and User-Adapted Interaction
Using interest and transition models to predict visitor locations in museums
AI Communications - Recommender Systems
Non-intrusive Personalisation of the Museum Experience
UMAP '09 Proceedings of the 17th International Conference on User Modeling, Adaptation, and Personalization: formerly UM and AH
Content-based recommendation systems
The adaptive web
CHIP demonstrator: semantics-driven recommendations and museum tour generation
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
A user-and item-aware weighting scheme for combining predictive user models
UMAP'10 Proceedings of the 18th international conference on User Modeling, Adaptation, and Personalization
GECKOmmender: personalised theme and tour recommendations for museums
UMAP'12 Proceedings of the 20th international conference on User Modeling, Adaptation, and Personalization
A folksonomy-based recommender system for personalized access to digital artworks
Journal on Computing and Cultural Heritage (JOCCH)
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Advances in mobile computing and user modelling have enabled technologies that help museum visitors select personally interesting exhibits to view. This is done by generating personalised exhibit recommendations on the basis of non-intrusive observations of visitors' behaviour in the physical museum space. We describe a simple methodology for manually annotating museum exhibits with bags of keywords (viewed as item features), and present two personalised keyword-based models for predicting a visitor's viewing times of unseen exhibits from his/her viewing times at visited exhibits (viewing time is indicative of interest). Our models were evaluated with a real-world dataset of visitor pathways collected by tracking visitors in a museum. Both models achieve a higher predictive accuracy than a non-personalised baseline, and perform at least as well as a nearest-neighbour collaborative filter.