Skip to main content

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5706))

Included in the following conference series:

Abstract

RAVE (Real-time Answer Validation Engine) is a logic-based answer validator/selector designed for real-time question answering. Instead of proving a hypothesis for each answer, RAVE uses logic only for checking if a considered passage supports a correct answer at all. In this way parsing of the answers is avoided, yielding low validation/selection times. Machine learning is used for assigning local validation scores based on logical and shallow features. The subsequent aggregation of these local scores strives to be robust to duplicated information in the support passages. To achieve this, the effect of aggregation is controlled by the lexical diversity of the support passages for a given answer.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Rodrigo, A., Peñas, A., Verdejo, F.: Overview of the Answer Validation Exercise 2008. In: Peters, C., et al. (eds.) CLEF 2008. LNCS, vol. 5706, pp. 296–313. Springer, Heidelberg (2009)

    Google Scholar 

  2. Hartrumpf, S., Glöckner, I., Leveling, J.: Efficient question answering with question decomposition and multiple answer streams. In: Peters, C., et al. (eds.) CLEF 2008. LNCS, vol. 5706, pp. 421–428. Springer, Heidelberg (2009)

    Google Scholar 

  3. Glöckner, I., Pelzer, B.: Combining logic and machine learning for answering questions. In: Peters, C., et al. (eds.) CLEF 2008. LNCS, vol. 5706, pp. 401–408. Springer, Heidelberg (2009)

    Google Scholar 

  4. Glöckner, I.: Filtering and fusion of question-answering streams by robust textual inference. In: Proceedings of KRAQ 2007, Hyderabad, India (2007)

    Google Scholar 

  5. Glöckner, I.: Towards logic-based question answering under time constraints. In: Proc. 2008 IAENG Int. Conf. on Artificial Intelligence and Applications (2008)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Glöckner, I. (2009). RAVE: A Fast Logic-Based Answer Validator. In: Peters, C., et al. Evaluating Systems for Multilingual and Multimodal Information Access. CLEF 2008. Lecture Notes in Computer Science, vol 5706. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04447-2_56

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-04447-2_56

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04446-5

  • Online ISBN: 978-3-642-04447-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics