Turkish Information Retrieval: Past Changes Future

  • Fazli Can
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4243)


One of the most exciting accomplishments of computer science in the lifetime of this generation is the World Wide Web. The Web is a global electronic publishing medium. Its size has been growing with an enormous speed for over a decade. Most of its content is objectionable, but it also contains a huge amount of valuable information. The Web adds a new dimension to the concept of information explosion and tries to solve the very same problem by information retrieval systems known as Web search engines. We briefly review the information explosion problem and information retrieval systems, convey the past and state of the art in Turkish information retrieval research, illustrate some recent developments, and propose some future actions in this research area in Turkey.


Information Retrieval Vector Space Model Information Retrieval System Test Collection Information Explosion 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Varian, H.R.: Universal Access to Information. Com. of the ACM 48(10), 65–66 (2005)CrossRefGoogle Scholar
  2. 2.
    Bush, V.: As We Think. The Atlantic Monthly 176(1), 101–108 (1945)Google Scholar
  3. 3.
    de Solla Price, D.: Little Science, Big Science...and Beyond. Columbia University Press, New York (1986) (originally published in 1963)Google Scholar
  4. 4.
    Knuth, D.E.: The Art of Computer Programming. Sorting and Searching, vol. 3. Addison-Wesley, Reading (1973)Google Scholar
  5. 5.
    Stefik, M.: The Internet Edge. MIT Press, Cambridge (1999)Google Scholar
  6. 6.
    Saracevic, T.: Information Science. Journal of the American Society for Information Science 50(12), 1051–1063 (1999)CrossRefGoogle Scholar
  7. 7.
    Toffler, A.: Future Shock. Bantam Books, New York (1990) (originally published: 1970)Google Scholar
  8. 8.
    Witten, I.H., Moffat, A., Bell, T.C.: Managing Gigabytes Compressing and Indexing Documents and Images, 2nd edn. Morgan Kaufmann Publishers, San Francisco (1999)Google Scholar
  9. 9.
    Gemmell, J., Bell, G., Lueder, R.: MyLifeBits: a Personal Database for Everything. Com. of the ACM 49(1), 89–95 (2006)Google Scholar
  10. 10.
    Salton, G.: Automatic Text Processing: the Transformation, Analysis and Retrieval of Information by Computer. Addison Wesley, Reading (1989)Google Scholar
  11. 11.
    Brin, S., Page, L.: The anatomy of a large scale hypertextual Web search engine. Computer Networks and ISDN Systems 30(1-7), 107–117 (1998)CrossRefGoogle Scholar
  12. 12.
    Bitirim, Y., Tonta, Y., Sever, H.: Information Retrieval Effectiveness of Turkish Search Engines. In: Yakhno, T. (ed.) ADVIS 2002. LNCS, vol. 2457, pp. 93–103. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  13. 13.
    Baeza-Yates, R., Ribeiro-Neto, B.: Modern Information Retrieval. Addison-Wesley, Reading (1999)Google Scholar
  14. 14.
    Köksal, A.: Tümüyle Özdevimli Deneysel Bir Belge Dizinleme ve Erisim Dizgesi: TÜRDER. In: The Proceedings of 3. Ulusal Bilisim, Kurultayi, Ankara, Turkey, pp. 37–44 (1981)Google Scholar
  15. 15.
    Solak, A., Can, F.: Effects of Stemming on Turkish Text Retrieval. In: Int. Symposium on Computer and Information Sciences (ISCIS), pp. 49–56 (1994)Google Scholar
  16. 16.
    Sever, H., Bitirim, Y.: FindStem: Analysis and Evaluation of Stemming algorithms for Turkish. In: Nascimento, M.A., de Moura, E.S., Oliveira, A.L. (eds.) SPIRE 2003. LNCS, vol. 2857, pp. 238–251. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  17. 17.
    Pembe, F.C., Say, A.C.C.: A Linguistically Motivated Information Retrieval System for Turkish. In: Aykanat, C., Dayar, T., Körpeoğlu, İ. (eds.) ISCIS 2004. LNCS, vol. 3280, pp. 741–750. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  18. 18.
    Voorhees, E.: Overview of TREC 2004 (accessed on June 16, 2006),
  19. 19.
    Salton, G., Buckley, C.: Term Weighting Approaches in Automatic Text Retrieval. Information Processing and Management 24, 513–523 (1988)CrossRefGoogle Scholar
  20. 20.
    Can, F., Kocberber, S., Balcik, E., Kaynak, C., Ocalan, H.C., Vursavas, O.M.: First Large Scale Information Retrieval Experiments on Turkish Texts (Poster paper). In: Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Seattle, Washington (to appear, 2006)Google Scholar
  21. 21.
    Radev, D., Otterbacher, J., Winkel, A., Blair-Goldensohn, S.: NewsInEssence: Summarizing Online News Topics. Com. of the ACM 48(10), 95–98 (2005)CrossRefGoogle Scholar
  22. 22.
    Hafer, M.A., Weiss, S.F.: Word Segmentation by Letter Successor Varieties. Infor. Stor. Retr. 10, 371–385 (1974)CrossRefGoogle Scholar
  23. 23.
    Oflazer, K.: Two-level Description of Turkish Morphology. Literary and Linguistic Computing 9(2), 137–148 (1994)CrossRefGoogle Scholar
  24. 24.
    Altintas, K., Can, F., Patton, J.M.: Language Change Quantification Using Time-Separated Parallel Translations. Literary and Linguistic Computing (accepted)Google Scholar
  25. 25.
    Buckley, C., Voorhees, E.M.: Retrieval Evaluation with Incomplete Information. In: Proceedings of the 27th annual international ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 25–32 (2004)Google Scholar
  26. 26.
    Mowshowitz, A., Kawaguchi, A.: Assessing Bias in Search Engines. Information Processing and Management 38(1), 141–156 (2002)MATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Fazli Can
    • 1
  1. 1.Bilkent Information Retrieval Group, Department of Computer EngineeringBilkent UniversityBilkent, AnkaraTurkey

Personalised recommendations