The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
HLT '02 Proceedings of the second international conference on Human Language Technology Research
MarcoPolo: a community system for sharing and integrating travel information on maps
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Cross-media topic mining on wikipedia
Proceedings of the 21st ACM international conference on Multimedia
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In Web 2.0, users have generated and shared massive amounts of resources in various media formats, such as news, blogs, audios, photos and videos. The abundance and diversity of the resources call for better integration to improve the accessibility. A straightforward approach is to link the resources via tags so that resources from different modals sharing the same tag can be connected as a graph structure. This naturally motivates a new kind of information retrieval system, named cross-modal resource search, in which given a query object from any modal, all the related resources from other modals can be retrieved in a convenient manner. However, due to the tag homonym and synonym, such an approach returns results of low quality because resources with the same tag but not semantically related will be directly connected as well. In this paper, we propose to build the resource graph and perform query processing by exploiting Wikipedia. We construct a concept middle-ware between the layer of tags and resources to fully capture the semantic meaning of the resources. Such a cross-modal search system based on Wikipedia, named Crew, is built and demonstrates promising search results.