Compare&contrast: using the web to discover comparable cases for news stories
Proceedings of the 16th international conference on World Wide Web
Using generalization of syntactic parse trees for taxonomy capture on the web
ICCS'11 Proceedings of the 19th international conference on Conceptual structures for discovering knowledge
Machine learning of syntactic parse trees for search and classification of text
Engineering Applications of Artificial Intelligence
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The web has become an important medium for news delivery and consumption. Fresh content about a variety of topics and events is constantly being created and published on the web by many sources. As intuitively understood by readers, and studied in journalism, news articles produced by different social groups present different attitudes towards and interpretations of the same news issues. In this paper, we propose a new paradigm for aggregating news articles according to the news sources related to the stakeholders of the news issues. We implement this paradigm in a prototype system called LocalSavvy. The system provides users the capability to aggregate and browse various local views about the news issues in which they are interested.