Hybrid Recommender Systems: Survey and Experiments
User Modeling and User-Adapted Interaction
Discovering Frequent Closed Itemsets for Association Rules
ICDT '99 Proceedings of the 7th International Conference on Database Theory
Mining Generalized Association Rules
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Towards a Better Understanding of Context and Context-Awareness
HUC '99 Proceedings of the 1st international symposium on Handheld and Ubiquitous Computing
Proceedings of the 2003 conference on Designing for user experiences
Incorporating contextual information in recommender systems using a multidimensional approach
ACM Transactions on Information Systems (TOIS)
An Introduction to RFID Technology
IEEE Pervasive Computing
A privacy preserving web recommender system
Proceedings of the 2006 ACM symposium on Applied computing
Using Context to Improve Predictive Modeling of Customers in Personalization Applications
IEEE Transactions on Knowledge and Data Engineering
Context-aware recommender systems
Proceedings of the 2008 ACM conference on Recommender systems
Efficient incremental mining of top-K frequent closed itemsets
DS'07 Proceedings of the 10th international conference on Discovery science
An Alignment Approach for Context Prediction Tasks in UbiComp Environments
IEEE Pervasive Computing
Understanding context before using it
CONTEXT'05 Proceedings of the 5th international conference on Modeling and Using Context
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We propose an approach to context-aware advertising in which context is defined by the products currently used by a consumer. Unlike more traditional approaches, consumers are neither identified nor tracked; instead, products are tagged. An interesting use-case scenario for this model is a product-aware outdoor advertising system that dynamically selects a product to advertise based on the products identified for one person or a group of people nearby. For example, RFID tags integrated into clothing of someone passing by a digital billboard could allow for determining preferences regarding style, fashion and brands. This information would be used by a digital billboard with an RFID reader to recommend and advertise complementary and other products. There would be no inherent connection between product information and the identity of the consumer; and therefore the privacy of the consumer would not be violated. Tagging and tracking of consumer products provides opportunities for more personalized and engaging marketing experiences without introducing a privacy risk.