Web content summarization using social bookmarking service

In this paper, we propose a novel web content summarization method that creates a text summary by exploiting user feedback (comments, annotations etc.) in the social bookmarking service. We first analyze the feasibility to utilize user feedback in the summarization, and then demonstrate how the social summary which best represents the topics of the web content can be generated. Performance evaluations on our method are conducted by comparing its output summary with the manual summaries generated by human evaluators.