Spark: top-k keyword query in relational databases
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
World explorer: visualizing aggregate data from unstructured text in geo-referenced collections
Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Crew: cross-modal resource searching by exploiting wikipedia
Proceedings of the international conference on Multimedia
Computing minimum diameter color-spanning sets
FAW'10 Proceedings of the 4th international conference on Frontiers in algorithmics
NP-completeness of spreading colored points
COCOA'10 Proceedings of the 4th international conference on Combinatorial optimization and applications - Volume Part I
A cross-service travel engine for trip planning
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Computing minimum diameter color-spanning sets is hard
Information Processing Letters
Supporting top-K item exchange recommendations in large online communities
Proceedings of the 15th International Conference on Extending Database Technology
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The tagging technique has been widely applied in existing Web 2.0 systems, where users label resources with tags for effective classification and efficient retrieval of resources. Location-aware geographical tags (geo-tags) are required if users want to mark location-sensitive resources to digital maps. Large volumes of different kinds of user-created tags pose challenges to the effective organization of community resources using tags. Issues such as guaranteeing the quality of tags and supporting various tag-based queries emerge. In this demo, we present MarcoPolo, a Web 2.0 community system that allows users to define the hierarchical textual geo-tags and mark resources to a map using geo-tags. Statistical and feedback mechanisms are applied to guarantee the quality of tags (including geo-tags). The MarcoPolo system provides two effective interfaces for users to browse and search resources: one is the keyword-based interface and the other is the map-based interface.