Skip to main content

A Semantic Search Framework for Document Retrievals (Literature, Art and History) Based on Thesaurus Multiwordnet Like

  • Conference paper
  • 2779 Accesses

Part of the Lecture Notes in Computer Science book series (LNTCS,volume 6838)

Abstract

The aim of this paper is to show the application of a Thesaurus based approach to several issues of interest for an Italian Publishing House. Final experimental results reveal good performance in terms of rate of retrieval and recall and then encourage the prosecution of the multidisciplinary research.

Keywords

  • Thesaurus
  • Multi-Wordnet
  • Monte Carlo Method
  • retrieval

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (Canada)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (Canada)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (Canada)
  • 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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Tumer, D., Shah, M.A., Bitirim, Y.: An Empirical Evaluation on Semantic Search Performance of Keyword-Based and Semantic Search Engines. Google, Yahoo, Msn and Hakia, Internet Monitoring and Protection. In: ICIMP 2009, pp. 51–55 (2009)

    Google Scholar 

  2. Pianta, E., et al.: Multiwordnet Developing an Aligned Multilingual Database. In: Proceedings of the 1st International WordNet Conf., pp. 293–302 (2002)

    Google Scholar 

  3. Cascini, E.: Considerazioni Sulla Variabilità Di Un Processo Di Misura Con Una Applicazione Nell’area Della Customer Satisfaction. Sei Sigma & Qualità 1(2), 18–210 (2006)

    MathSciNet  Google Scholar 

  4. Kassim, J., et al.: Introduction to Semantic Search Engine. In: International Conference on Electrical Engineering and Informatics, pp. 380–385 (2009)

    Google Scholar 

  5. Loganantharaj, R., et al.: An Ontology Based Semantic Literature Retrieval System. In: Proc. of the 19th IEEE Symp. on Computer-Based Medical Systems (2006)

    Google Scholar 

  6. He, R., Liu, L.: Educational Resource Sharing Model Based on Semantic Grid. Computational Intelligence and Software Engineering (2009)

    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

Bevilacqua, V., Santarcangelo, V., Magarelli, A., Bianco, A., Mastronardi, G., Cascini, E. (2011). A Semantic Search Framework for Document Retrievals (Literature, Art and History) Based on Thesaurus Multiwordnet Like. In: Huang, DS., Gan, Y., Bevilacqua, V., Figueroa, J.C. (eds) Advanced Intelligent Computing. ICIC 2011. Lecture Notes in Computer Science, vol 6838. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24728-6_62

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-24728-6_62

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24727-9

  • Online ISBN: 978-3-642-24728-6

  • eBook Packages: Computer ScienceComputer Science (R0)