Skip to main content
SpringerLink
Log in

Interactive Information Retrieval Algorithm for Wikipedia Articles

  • Conference paper
Intelligent Data Engineering and Automated Learning - IDEAL 2012 (IDEAL 2012)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7435))

Abstract

The article presents an algorithm for retrieving textual information in documents collection. The algorithm employs a category system that organizes the repository and using interaction with the user improves search precision. The algorithm was implemented for simple English Wikipedia and the first evaluation results indicates the proposed method can help to retrieve information from large document repositories.

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

Access this chapter

Log in via an institution
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. Baeza-Yates, R., Ribeiro-Neto, B., et al.: Modern information retrieval, vol. 463. ACM press, New York (1999)

    Google Scholar 

  2. Castells, P., Fernandez, M., Vallet, D.: An adaptation of the vector-space model for ontology-based information retrieval. IEEE Transactions on Knowledge and Data Engineering 19, 261–272 (2007)

    Article  Google Scholar 

  3. Kilicoglu, H., Fiszman, M., Rodriguez, A., Shin, D., Ripple, A., Rindflesch, T.: Semantic medline: A web application for managing the results of pubmed searches. In: Proceedings of the Third International Symposium for Semantic Mining in Biomedicine, pp. 69–76 (2008)

    Google Scholar 

  4. Raghavan, V., Bollmann, P., Jung, G.: A critical investigation of recall and precision as measures of retrieval system performance. ACM Transactions on Information Systems (TOIS) 7, 205–229 (1989)

    Article  Google Scholar 

  5. Miller, G.A., Beckitch, R., Fellbaum, C., Gross, D., Miller, K.: Introduction to WordNet: An On-line Lexical Database. Cognitive Science Laboratory, Princeton University Press (1993)

    Google Scholar 

  6. Jiang, J., Conrath, D.: Semantic similarity based on corpus statistics and lexical taxonomy. Arxiv preprint cmp-lg/9709008 (1997)

    Google Scholar 

  7. Deerwester, S., Dumais, S., Furnas, G., Landauer, T., Harshman, R.: Indexing by latent semantic analysis. Journal of the American Society for Information Science 41, 391–407 (1990)

    Article  Google Scholar 

  8. Xu, J., Croft, W.: Query expansion using local and global document analysis. In: Proceedings of the 19th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 4–11. ACM (1996)

    Google Scholar 

  9. Majewski, P., Szymański, J.: Text Categorization with Semantic Commonsense Knowledge: First Results. In: Ishikawa, M., Doya, K., Miyamoto, H., Yamakawa, T. (eds.) ICONIP 2007, Part II. LNCS, vol. 4985, pp. 769–778. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  10. Ceglowski, M., Coburn, A., Cuadrado, J.: Semantic search of unstructured data using contextual network graphs. National Institute for Technology and Liberal Education 10 (2003)

    Google Scholar 

  11. Cui-ru, W., Chun-hong, D.: An Improved Density-based DBSCAN Clustering Algorithm. Journal of Guangxi Normal University (Natural Science Edition) 4 (2007)

    Google Scholar 

  12. Rosell, M.: Introduction to text clustering (2008)

    Google Scholar 

  13. Manning, C.D., Raghavan, P., Schütze, H.: Introduction to Information Retrieval. Cambridge University Press, New York (2008)

    Book  MATH  Google Scholar 

  14. Szymanski, J., Duch, W.: Information Retrieval with Semantic Memory Model. Cognitive Systems Research (2011)

    Google Scholar 

  15. Voorhees, E.: Using WordNet to disambiguate word senses for text retrieval. In: Proceedings of the 16th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 171–180. ACM, New York (1993)

    Chapter  Google Scholar 

  16. Szymański, J., Mizgier, A., Szopiński, M., Lubomski, P.: Ujednoznacznianie słow przy użyciu słownika WordNet. Wydawnictwo Naukowe PG TI 2008 18, 89–195 (2008)

    Google Scholar 

  17. Duch, W., Matykiewicz, P., Pestian, J.: Neurolinguistic approach to natural language processing with applications to medical text analysis. Neural Networks 21(10), 1500–1510 (2008)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Systems Architecture, Gdańsk University of Technology, Poland

    Julian Szymański

Authors
  1. Julian Szymański
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. School of Electrical and Electronic Engineering, The University of Manchester, M13 9PL, Manchester, UK

    Hujun Yin

  2. Department of Electrical Engineering, Federal University of Rio Grande do Norte, Lagoa Nova, 59072-970, Natal, RN, Brazil

    José A. F. Costa

  3. Department of Teleinformatics Engineering, Federal University of Ceará, Campus of Pici, CP 6005, 60455-760, Fortaleza, CE, Brazil

    Guilherme Barreto

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Szymański, J. (2012). Interactive Information Retrieval Algorithm for Wikipedia Articles. In: Yin, H., Costa, J.A.F., Barreto, G. (eds) Intelligent Data Engineering and Automated Learning - IDEAL 2012. IDEAL 2012. Lecture Notes in Computer Science, vol 7435. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32639-4_25

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-32639-4_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32638-7

  • Online ISBN: 978-3-642-32639-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation