Skip to main content

Information Retrieval Using a Macedonian Test Collection for Question Answering

  • Conference paper
ICT Innovations 2010 (ICT Innovations 2010)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 83))

Included in the following conference series:

Abstract

Question answering systems solve many of the problems that users encounter when searching for focused information on the web and elsewhere. However, these systems cannot always adequately understand the user’s question posed in a natural language, primarily because any particular language has its own specifics that have to be taken into account in the search process. When designing a system for answering questions posed in a natural language, there is a need of creating an appropriate test collection that will be used for testing the system’s performance, as well as using an information retrieval method that will effectively answer questions for that collection. In this paper, we present a test collection we developed for answering questions in Macedonian language. We use this collection to test the performance of the vector space model with pivoted document length normalization. Preliminary experimental results show that our test collection can be effectively used to answer multiple-choice questions in Macedonian language.

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 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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. Belkin, N.J., Vickery, A.: Interaction in information systems. The British Library (1985)

    Google Scholar 

  2. Chowdhury, A., Catherine McCabe, M., Grossman, D., Frieder, O.: Document normalization revisited. In: Proceedings of the ACM-SIGIR International Conference on Research and Development in Information Retrieval, Tampere, Finland, pp. 381–382 (2002)

    Google Scholar 

  3. Dang, H.T., Kelly, D., Lin, J.: Overview of the TREC 2007 Question Answering Track. In: NIST Special Publication 500-274: The Sixteenth Text REtrieval Conference Proceedings (TREC 2007), Gaithersburg, Maryland (2007)

    Google Scholar 

  4. Kwok, C., Etzioni, O., Weld, D.: Scaling Question Answering to the Web. ACM Transactions on Information Systems 19(3), 242–262 (2001)

    Article  Google Scholar 

  5. Magnini, B., Negri, M., Prevete, R., Tanev, H.: Mining the Web to validate answers to natural language questions. In: Proceedings of Data Mining 2002, Bologna, Italy (2002)

    Google Scholar 

  6. Manning, C., Raghavan, P., Schutze, H.: Introduction to Information Retrieval. Cambridge University Press, Cambridge (2008)

    Book  MATH  Google Scholar 

  7. Salton, G., Wong, A., Yang, C.S.: A vector space model for automatic indexing. Communications of the ACM 18(11), 613–620 (1975)

    Article  MATH  Google Scholar 

  8. Singhal, A., Buckley, C., Mitra, M.: Pivoted document length normalization. In: Proceedings of the ACM-SIGIR International Conference on Research and Development in Information Retrieval, Zurich, Switzerland, pp. 21–29 (1996)

    Google Scholar 

  9. Sparck Jones, K., Walker, S., Robertson, S.E.: A probabilistic model of information retrieval: Development and comparative experiments. Parts 1 and 2. Information Processing and Management 36(6), 779–840 (2000)

    Article  Google Scholar 

  10. Sultan, M.: Multiple Choice Question Answering, MSc thesis, University of Sheffield (2006)

    Google Scholar 

  11. Witten, I.H., Moffat, A., Bell, T.C.: Managing Gigabytes: Compressing and Indexing Documents and Images, 2nd edn. Morgan Kaufmann Publishers, San Francisco (1999)

    MATH  Google Scholar 

  12. Zhai, C., Lafferty, J.: A study of smoothing methods for language models applied to information retrieval. ACM Transactions on Information Systems 22(2), 179–214 (2004)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Armenska, J., Tomovski, A., Zdravkova, K., Pehcevski, J. (2011). Information Retrieval Using a Macedonian Test Collection for Question Answering. In: Gusev, M., Mitrevski, P. (eds) ICT Innovations 2010. ICT Innovations 2010. Communications in Computer and Information Science, vol 83. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19325-5_21

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-19325-5_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-19324-8

  • Online ISBN: 978-3-642-19325-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics