Context and learning in novelty detection

Authors:
Barry Schiffman;Kathleen R. McKeown
Affiliations:
Columbia University, New York, N.Y.;Columbia University, New York, N.Y.
Venue:
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Year:
2005

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Abstract

We demonstrate the value of using context in a new-information detection system that achieved the highest precision scores at the Text Retrieval Conference's Novelty Track in 2004. In order to determine whether information within a sentence has been seen in material read previously, our system integrates information about the context of the sentence with novel words and named entities within the sentence, and uses a specialized learning algorithm to tune the system parameters.