• Documents
  • Authors
  • Tables
  • Log in
  • Sign up
  • MetaCart
  • DMCA
  • Donate

CiteSeerX logo

Advanced Search Include Citations
Advanced Search Include Citations | Disambiguate

DMCA

An Answer Updating Approach to Novelty Detection

Cached

  • Download as a PDF

Download Links

  • [ciir.cs.umass.edu]
  • [maroo.cs.umass.edu]
  • [ciir-publications.cs.umass.edu]
  • [maroo.cs.umass.edu]

  • Save to List
  • Add to Collection
  • Correct Errors
  • Monitor Changes
by Xiaoyan Li
  • Summary
  • Citations
  • Active Bibliography
  • Co-citation
  • Clustered Documents
  • Version History

BibTeX

@MISC{Li_ananswer,
    author = {Xiaoyan Li},
    title = {An Answer Updating Approach to Novelty Detection},
    year = {}
}

Share

Facebook Twitter Reddit Bibsonomy

OpenURL

 

Abstract

The detection of new and novel information in a document stream is an important component of potential applications. This paper describes an answer updating approach to novelty detection at the sentence level. Specifically, we explore the use of questionanswering techniques for novelty detection. New information is defined as new/previously unseen answers to questions representing a user’s information need. A sentence is treated as novel sentence if the system believes that it may contain a previously unseen answer to the question. In our answer updating approach, there are two important steps: question formulation and new answer detection. Experiments were carried out on data from the TREC 2003 novelty track using the proposed approach. The results show that the proposed answer updating approach outperforms all three baselines in terms of precision at low recall.

Keyphrases

novelty detection    answer updating approach    unseen answer    user information need    new answer detection    approach outperforms    sentence level    novel information    new information    document stream    important component    novelty track    question formulation    important step    low recall    potential application    novel sentence   

Powered by: Apache Solr
  • About CiteSeerX
  • Submit and Index Documents
  • Privacy Policy
  • Help
  • Data
  • Source
  • Contact Us

Developed at and hosted by The College of Information Sciences and Technology

© 2007-2019 The Pennsylvania State University