document: Generating diverse and representative image search results for landmarks Can we leverage the community-contributed collections of rich media on the web to automatically generate representative and diverse views of the world 's landmarks ? We use a combination of context - and content-based tools to generate representative sets of images for location-driven features and landmarks , a common search task . To do that , we using location and other metadata , as well as tags associated with images , and the images ' visual features . We present an approach to extracting tags that represent landmarks . We show how to use unsupervised methods to extract representative views and images for each landmark . This approach can potentially scale to provide better search and representation for landmarks , worldwide . We evaluate the system in the context of image search using a real-life dataset of 110,000 images from the San Francisco area .
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