First large-scale information retrieval experiments on turkish texts

ABSTRACT

We present the results of the first large-scale Turkish information retrieval experiments performed on a TREC-like test collection. The test bed, which has been created for this study, contains 95.5 million words, 408,305 documents, 72 ad hoc queries and has a size of about 800MB. All documents come from the Turkish newspaper Milliyet. We implement and apply simple to sophisticated stemmers and various query-document matching functions and show that truncating words at a prefix length of 5 creates an effective retrieval environment in Turkish. However, a lemmatizer-based stemmer provides significantly better effectiveness over a variety of matching functions.

REFERENCES

• 1: Altintas, K., Can, F., Patton, J. M. Language change quantification using time-separated parallel translations. Literary and Linguistic Computing (resubmitted after rev.).
• 2: Chris Buckley , Ellen M. Voorhees, Retrieval evaluation with incomplete information, Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval, July 25-29, 2004, Sheffield, United Kingdom [doi>10.1145/1008992.1009000]
• 3: Hafer, M. A., Weiss, S. F. Word segmentation by letter successor varieties. Infor. Stor. Retr. 10, 371--385, 1974.
• 4: Gerard Salton , Christopher Buckley, Term-weighting approaches in automatic text retrieval, Information Processing and Management: an International Journal, v.24 n.5, p.513-523, 1988 [doi>10.1016/0306-4573(88)90021-0]
• 5: Sever, H., Bitirim Y. FindStem: analysis and evaluation of a Turkish stemming algorithm. LNCS 2857: 238--251, 2003.
• 6: Sever, H., Tonta, Y. Truncation of content terms for Turkish. CICLing Feb. 2006, Mexico (to appear).
• 7: Solak, A., Can, F., Effects of stemming on Turkish text retrieval. ISCIS Conf., pp. 49--56, 1994.
• 8: Ian H. Witten , Alistair Moffat , Timothy C. Bell, Managing gigabytes (2nd ed.): compressing and indexing documents and images, Morgan Kaufmann Publishers Inc., San Francisco, CA, 1999

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.1 Content Analysis and Indexing
          Subjects: Indexing methods

Additional Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval
          Subjects: Selection process; Search process

General Terms:
Experimentation, Performance

Keywords:
IR test collection creation, lemmatizer, stemming, turkish