PITTCULT: trust-based cultural event recommender
Proceedings of the 2008 ACM conference on Recommender systems
Item popularity and recommendation accuracy
Proceedings of the fifth ACM conference on Recommender systems
Bayesian latent variable models for collaborative item rating prediction
Proceedings of the 20th ACM international conference on Information and knowledge management
Entertainment on the go: finding things to do and see while visiting distributed events
Proceedings of the 4th Information Interaction in Context Symposium
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Distributed events are collections of events taking place within a small area over the same time period and relating to a single topic. There are often a large number of events on offer and the times in which they can be visited are heavily constrained, therefore the task of choosing events to visit and in which order can be very difficult. In this work we investigate how visitors can be assisted by means of a recommender system via 2 large-scale naturalistic studies (n=860 and n=1047). We show that a recommender system can influence users to select events that result in tighter and more compact routes, thus allowing users to spend less time travelling and more time visiting events.