Retrieval and novelty detection at the sentence level

  • Authors:
  • James Allan;Courtney Wade;Alvaro Bolivar

  • Affiliations:
  • University of Massachusetts, Amherst, MA;University of Massachusetts, Amherst, MA;University of Massachusetts, Amherst, MA

  • Venue:
  • Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
  • Year:
  • 2003

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Abstract

Previous research in novelty detection has focused on the task of finding novel material, given a set or stream of documents on a certain topic. This study investigates the more difficult two-part task defined by the TREC 2002 novelty track: given a topic and a group of documents relevant to that topic, 1) find the relevant sentences from the documents, and 2) find the novel sentences from the collection of relevant sentences. Our research shows that the former step appears to be the more difficult part of this task, and that the performance of novelty measures is very sensitive to the presence of non-relevant sentences.