Using collaborative filtering to weave an information tapestry
Communications of the ACM - Special issue on information filtering
Mining, indexing, and querying historical spatiotemporal data
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Why we tag: motivations for annotation in mobile and online media
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Towards automatic extraction of event and place semantics from flickr tags
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Exploiting real world knowledge in ubiquitous applications
Personal and Ubiquitous Computing
Robust collaborative filtering
Proceedings of the 2007 ACM conference on Recommender systems
Generating diverse and representative image search results for landmarks
Proceedings of the 17th international conference on World Wide Web
Gazetiki: automatic creation of a geographical gazetteer
Proceedings of the 8th ACM/IEEE-CS joint conference on Digital libraries
World-scale mining of objects and events from community photo collections
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
Proceedings of the 18th international conference on World wide web
Mining city landmarks from blogs by graph modeling
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Mining tourist information from user-supplied collections
Proceedings of the 18th ACM conference on Information and knowledge management
Generating tourism path from trajectories and geo-photos
WISE'12 Proceedings of the 13th international conference on Web Information Systems Engineering
Discovering local attractions from geo-tagged photos
Proceedings of the 28th Annual ACM Symposium on Applied Computing
Personalized intra- and inter-city travel recommendation using large-scale geotags
Proceedings of the 2nd ACM international workshop on Geotagging and its applications in multimedia
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Photo sharing platforms users often annotate their trip photos with landmark names. These annotations can be aggregated in order to recommend lists of popular visitor attractions similar to those found in classical tourist guides. However, individual tourist preferences can vary significantly so good recommendations should be tailored to individual tastes. Here we pose this visit personalization as a collaborative filtering problem. We mine the record of visited landmarks exposed in online user data to build a user-user similarity matrix. When a user wants to visit a new destination, a list of potentially interesting visitor attractions is produced based on the experience of like-minded users who already visited that destination. We compare our recommender to a baseline which simulates classical tourist guides on a large sample of Flickr users.