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Rich interfaces for reading news on the web
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International Conference on Intelligent User Interfaces archive
Proceedings of the 13th international conference on Intelligent user interfaces table of contents
Sanibel Island, Florida, USA
SESSION: Summarization table of contents
Pages 27-36  
Year of Publication: 2009
ISBN:978-1-60558-168-2
Authors
Earl J. Wagner  Northwestern University, Evanston, IL, USA
Jiahui Liu  Northwestern University, Evanston, IL, USA
Larry Birnbaum  Northwestern University, Evanston, IL, USA
Kenneth D. Forbus  Northwestern University, Evanston, IL, USA
Sponsors
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
ACM: Association for Computing Machinery
SIGART: ACM Special Interest Group on Artificial Intelligence
Publisher
ACM  New York, NY, USA
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ABSTRACT

Using content-specific models to guide information retrieval and extraction can provide richer interfaces to end-users for both understanding the context of news events and navigating related news articles. In this paper we discuss a system, Brussell, that uses semantic models to organize retrieval and extraction results, generating both storylines explaining how news event situations unfold and also biographical sketches of the situation participants. We generalize these models to introduce a new category of knowledge representation, an explanatory structure, that can scale up to include information from hundreds of documents, yet still provide model-based UI support to end-users. An informal survey of business news suggests the broad prevalence of news event situations indicating Brussell's potential utility, while an evaluation quantifies its performance in finding kidnapping situations.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Earl J. Wagner: colleagues
Jiahui Liu: colleagues
Larry Birnbaum: colleagues
Kenneth D. Forbus: colleagues