Advertisement

Multilingual Adaptive Search for Digital Libraries

  • M. Rami Ghorab
  • Johannes Leveling
  • Séamus Lawless
  • Alexander O’Connor
  • Dong Zhou
  • Gareth J. F. Jones
  • Vincent Wade
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6966)

Abstract

We describe a framework for Adaptive Multilingual Information Retrieval (AMIR) which allows multilingual resource discovery and delivery using on-the-fly machine translation of documents and queries. Result documents are presented to the user in a contextualised manner. Challenges and affordances of both adaptive and multilingual IR, with a particular focus on digital libraries, are detailed. The framework components are motivated by a series of results from experiments on query logs and documents from The European Library. We conclude that factoring adaptivity and multilinguality aspects into the search process can enhance the user’s experience with online digital libraries.

Keywords

Digital Library Machine Translation Query Expansion Mean Average Precision Parallel Corpus 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Brusilovsky, P.: Adaptive hypermedia. User Modeling and User-Adapted Interaction 11(1), 87–110 (2001)CrossRefzbMATHGoogle Scholar
  2. 2.
    Chirita, P.A., Firan, C.S., Nejdl, W.: Personalized query expansion for the web. In: SIGIR 2007, pp. 7–14. ACM, New York (2007)Google Scholar
  3. 3.
    Ghorab, M.R., Leveling, J., Zhou, D., Jones, G.J.F., Wade, V.: Identifying common user behaviour in multilingual search logs. In: Peters, C., Di Nunzio, G.M., Kurimo, M., Mostefa, D., Peñas, A., Roda, G. (eds.) CLEF 2009. LNCS, vol. 6241, pp. 518–525. Springer, Heidelberg (2010)Google Scholar
  4. 4.
    Gövert, N., Fuhr, N., Klas, C.P.: Daffodil: Distributed agents for user-friendly access of digital libraries. In: Borbinha, J.L., Baker, T. (eds.) ECDL 2000. LNCS, vol. 1923, pp. 352–355. Springer, Heidelberg (2000)CrossRefGoogle Scholar
  5. 5.
    Kriewel, S., Fuhr, N.: Adaptive search suggestions for digital libraries. In: Goh, D.H.L., Cao, T.H., Sølvberg, I., Rasmussen, E.M. (eds.) ICADL 2007. LNCS, vol. 4822, pp. 220–229. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  6. 6.
    Lawless, S., O’Connor, A., Mulwa, C.: A proposal for the evaluation of adaptive personalised information retrieval. In: CIRSE 2010, Milton Keynes, UK (2010)Google Scholar
  7. 7.
    Leveling, J., Ghorab, R., Magdy, W., Jones, G.J.F., Wade, V.: DCU-TCD@LogCLEF 2010: Re-ranking document collections and query performance estimation. In: CLEF 2010 LABs and Workshops, Notebook Papers, Padua, Italy, September 22-23 (2010)Google Scholar
  8. 8.
    Mandl, T., Agosti, M., Di Nunzio, G.M., Yeh, A., Mani, I., Doran, C., Schulz, J.M.: LogCLEF 2009: The CLEF 2009 multilingual logfile analysis track overview. In: Peters, C., Di Nunzio, G.M., Kurimo, M., Mostefa, D., Peñas, A., Roda, G. (eds.) CLEF 2009. LNCS, vol. 6241, pp. 508–517. Springer, Heidelberg (2010)Google Scholar
  9. 9.
    Raibulet, C., Masciadri, L.: Evaluation of dynamic adaptivity through metrics: An achievable target? In: WICSA/ECSA 2009, pp. 341–344 (2009)Google Scholar
  10. 10.
    Rigaux, P., Spyratos, N.: Metadata inference for document retrieval in a distributed repository. In: Maher, M.J. (ed.) ASIAN 2004. LNCS, vol. 3321, pp. 418–436. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  11. 11.
    Zhou, D., Lawless, S., Min, J., Wade, V.: A late fusion approach to cross-lingual document re-ranking. In: CIKM 2010, pp. 1433–1436. ACM, New York (2010)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • M. Rami Ghorab
    • 1
  • Johannes Leveling
    • 2
  • Séamus Lawless
    • 1
  • Alexander O’Connor
    • 1
  • Dong Zhou
    • 1
  • Gareth J. F. Jones
    • 2
  • Vincent Wade
    • 1
  1. 1.CNGL, Knowledge and Data Engineering Group, School of Computer Science & StatisticsTrinity College DublinDublin 2Ireland
  2. 2.CNGL, School of ComputingDublin City UniversityDublin 9Ireland

Personalised recommendations