Tell me more, not just "more of the same"

Francisco Iacobelli*, Lawrence A Birnbaum, Kristian J Hammond

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

19 Scopus citations


The Web makes it possible for news readers to learn more about virtually any story that interests them. Media outlets and search engines typically augment their information with links to similar stories. It is up to the user to determine what new information is added by them, if any. In this paper we present Tell Me More, a system that performs this task automatically: given a seed news story, it mines the web for similar stories reported by different sources and selects snippets of text from those stories which offer new information beyond the seed story. New content may be classified as supplying: additional quotes, additional actors, additional figures and additional information depending on the criteria used to select it. In this paper we describe how the system identifies new and informative content with respect to a news story. We also how that providing an explicit categorization of new information is more useful than a binary classification (new/not-new). Lastly, we show encouraging results from a preliminary evaluation of the system that validates our approach and encourages further study.

Original languageEnglish (US)
Title of host publicationIUI 2010 - Proceedings of the 14th ACM International Conference on Intelligent User Interfaces
Number of pages10
StatePublished - 2010
Event14th ACM International Conference on Intelligent User Interfaces, IUI 2010 - Hong Kong, China
Duration: Feb 7 2010Feb 10 2010

Publication series

NameInternational Conference on Intelligent User Interfaces, Proceedings IUI


Other14th ACM International Conference on Intelligent User Interfaces, IUI 2010
CityHong Kong


  • Dimensions of similarity
  • Information retrieval
  • New information detection

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction


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