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Context and Learning in Novelty Detection

McKeown, Kathleen; Schiffman, Barry

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.

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Academic Units
Computer Science
Publisher
Proceedings of HLT/EMNLP 2005
Published Here
June 27, 2013