Rich interfaces for reading news on the web

Authors:
Earl J. Wagner;Jiahui Liu;Larry Birnbaum;Kenneth D. Forbus
Affiliations:
Northwestern University, Evanston, IL, USA;Northwestern University, Evanston, IL, USA;Northwestern University, Evanston, IL, USA;Northwestern University, Evanston, IL, USA
Venue:
Proceedings of the 14th international conference on Intelligent user interfaces
Year:
2009

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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.