Comparison of hierarchic agglomerative clustering methods for document retrieval
The Computer Journal
End-user place annotation on mobile devices: a comparative study
CHI '06 Extended Abstracts on Human Factors in Computing Systems
A familiar face(book): profile elements as signals in an online social network
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Defining clusters from a hierarchical cluster tree
Bioinformatics
Using the wisdom of the crowds for keyword generation
Proceedings of the 17th international conference on World Wide Web
Flickr tag recommendation based on collective knowledge
Proceedings of the 17th international conference on World Wide Web
Identity construction on Facebook: Digital empowerment in anchored relationships
Computers in Human Behavior
Web-Based Measure of Semantic Relatedness
WISE '08 Proceedings of the 9th international conference on Web Information Systems Engineering
Spirittagger: a geo-aware tag suggestion tool mined from flickr
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
Citizen Sensing, Social Signals, and Enriching Human Experience
IEEE Internet Computing
Personalized Location-Based Recommendation Services for Tour Planning in Mobile Tourism Applications
EC-Web 2009 Proceedings of the 10th International Conference on E-Commerce and Web Technologies
Wikipedia-based semantic interpretation for natural language processing
Journal of Artificial Intelligence Research
Twarql: tapping into the wisdom of the crowd
Proceedings of the 6th International Conference on Semantic Systems
Exploiting geographical influence for collaborative point-of-interest recommendation
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
On the semantic annotation of places in location-based social networks
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Learning location naming from user check-in histories
Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Divergence measures based on the Shannon entropy
IEEE Transactions on Information Theory
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In recent years, location based services (LBS) have become very popular. The performance of LBS depends on number of factors including how well the places are described. Though LBS enable users to tag places, users rarely do so. On the other hand, users express their interests via online social networks. The common interests of a group of people that has visited a particular place can potentially provide further description for that place. In this work we present an approach that automatically assigns tags to places, based on interest profiles and visits or check-ins of users at places. We have evaluated our approach with real world datasets from popular social network services against a set of manually assigned tags. Experimental results show that we are able to derive meaningful tags for different places and that sets of tags assigned to places are expected to stabilise as more unique users visit places.