Light stemming approach for the French, Portuguese, German and Hungarian languages

Proceedings of the ACM Symposium on Applied Computing

Volumn 2, Issue , 2006, Pages 1031-1035

  Savoy, Jacques ^a  

^a UNIVERSITY OF NEUCHÂTEL   (Switzerland)

Author keywords

German; Hungarian; stemmer; Natural language processing; Portuguese; Stemming for French

Indexed keywords

COMPUTER SCIENCE; DATA ACQUISITION; STATISTICAL METHODS;

GERMAN; HUNGARIAN; STEMMER; PORTUGUESE; STEMMING FOR FRENCH;

NATURAL LANGUAGE PROCESSING SYSTEMS;

EID: 33751042434     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (18)

1. McNamee, P., and Mayfield, J. Character N-gram tokenization for European language text retrieval. IR Journal, 7(1-2), 2004, 73-97.
2. Lovins, J.B. Development of a stemming algorithm. Mechanical Translation and Computational Linguistics, 11(1), 1968, 22-31.
3. Porter, M.F. An algorithm for suffix stripping. Program, 14(3), 1980, 130-137.
4. Krovetz, R. Viewing morphology as an inference process. In Proceedings of the ACM-SIGIR. Pittsburgh, PA, 1993, 191-202.
5. Xu, J., and Croft, B. Corpus-based stemming using cooccurrence of word variants. ACM-TOIS, 16(1), 1998, 61-81.
6. Savoy, J. Stemming of French words based on grammatical category. JASIS, 44(1), 1993, 1-9.
7. Korenius, T., Laurikkala, J., Järvelin, K., and Juhola, M. Stemming and lemmatization in the clustering of Finnish text documents. In Proceedings of the ACM-CIKM. Washington, DC, 2004, 625-633.
8. Harman, D. How effective is suffixing? JASIS, 42(1), 1991, 7-15.
9. Di Nunzio, G.M., Ferro, N., Melucci, M., and Orio, N. Experiments to evaluate probabilistic models for automatic stemmer generation and query word translation. In Comparative Evaluation of Multilingual Information Access Systems. LNCS #3237, Springer, Berlin, 2004, 220-235.
10. Braschler, M., and Ripplinger, B. How effective is stemming and decompounding for German text retrieval? IR Journal, 7(3-4), 2004, 291-316.
11. Tomlinson, S. Lexical and algorithmic stemming compared for 9 European languages with Humminbird SearchServer™ at CLEF 2003. In Comparative Evaluation of Multilingual Information Access Systems. LNCS #3237, Springer-Verlag, Berlin, 2004, 286-300.
12. Kluck, M. The GIRT data in the evaluation of CLIR systems - from 1997 until 2003. In Comparative Evaluation of Multilingual Information Access Systems. LNCS #3237, Springer, Berlin, 2004, 376-390.
13. Savoy, J. Report on CLEF-2003 monolingual tracks. In Comparative Evaluation of Multilingual Information Access Systems. LNCS #3237, Springer, Berlin, 2004, 322-336.
14. Buckley, C., Singhal, A., Mitra, M., and Salton, G. New retrieval approaches using SMART. In Proceedings of TREC-4. Gaithersburg, MA, 1996, 25-48.
15. Singhal, A., Choi, J., Kindle, D., Lewis, D.D. & Pereira, F. (1999)..AT&T at TREC-7. In Proceedings TREC-7, Gaithersburg, MA, 1999, 239-251.
16. Robertson, S.E., Walker, S., and Beaulieu, M. Experimentation as a way of life: Okapi at TREC. IP&M, 36(1), 2000, 95-108.
17. Amati, G., and van Rijsbergen, C.J. Probabilistic models of information retrieval based on measuring the divergence from randomness. ACM-TOIS, 20(4), 2002, 357-389.
18. Savoy, J. Statistical inference in retrieval effectiveness evaluation. Information Processing &Management, 33(4), 1997, 495-512.