GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
Towards a Better Understanding of Context and Context-Awareness
HUC '99 Proceedings of the 1st international symposium on Handheld and Ubiquitous Computing
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
Incorporating contextual information in recommender systems using a multidimensional approach
ACM Transactions on Information Systems (TOIS)
CHI '05 Extended Abstracts on Human Factors in Computing Systems
IEEE Transactions on Knowledge and Data Engineering
Factorization meets the neighborhood: a multifaceted collaborative filtering model
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
From Web to Social Web: Discovering and Deploying User and Content Profiles
Exploiting contextual information in recommender systems
Proceedings of the 2008 ACM conference on Recommender systems
Context-aware recommender systems
Proceedings of the 2008 ACM conference on Recommender systems
Experimental comparison of pre- vs. post-filtering approaches in context-aware recommender systems
Proceedings of the third ACM conference on Recommender systems
Proceedings of the fourth ACM conference on Recommender systems
Managing dynamic context to optimize smart interactions and services
The smart internet
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Proceedings of the 2011 Conference of the Center for Advanced Studies on Collaborative Research
Situation-aware smarter commerce
CASCON '12 Proceedings of the 2012 Conference of the Center for Advanced Studies on Collaborative Research
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Daily-deal applications are popular implementations of on-line advertising strategies that offer products and services to users based on their personal profiles. The current implementations are effective but can frustrate users with irrelevant deals due to stale profiles. To exploit these applications fully, deals must become smarter and context-aware. This paper presents SmarterDeals, our deal recommendation system that exploits users' changing personal context information to deliver highly relevant offers. SmarterDeals relies on recommendation algorithms based on collaborative filtering, and SmarterContext, our adaptive context management framework. SmarterContext provides SmarterDeals with up-to-date information about users' locations and product preferences gathered from their past and present web interactions. For many deal categories the accuracy of SmarterDeals is between 3% and 8% better than the approaches we used as baselines. For some categories, and in terms of multiplicative relative performance, SmarterDeals outperforms related approaches by as much as 173.4%, and 37.5% on average.