Semantic Web Dog Food

Presented at: 20th International World Wide Web Conference (WWW2011)

by Pinaki Sinha

The volume of personal photos hosted on photo archives and social sharing platforms has been increasing exponentially. It is difficult to get an overview of a large collection of personal photos without browsing though the entire database manually. In this research, we propose a framework to generate representative subset summaries from photo collections hosted on web archives or social networks. We define salient properties of an effective photo summary and model summarization as an optimization of these properties, given the size constraints. We also introduce metrics for evaluating photo summaries based on their information content and the ability to satisfy user's information needs. Our experiments show that our summarization framework performs better than baseline algorithms.

Summarization of Archived and Shared Personal Photo Collections was presented at this event.

Keywords: Text Mining, World Wide Web

Resource URI on the dog food server: http://data.semanticweb.org/conference/www/2011/phd/summarization-of-archived-and-shared-personal-phot

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