The role of variance in term weighting for probabilistic information retrieval

International Conference on Information and Knowledge Management, Proceedings

Volumn , Issue , 2002, Pages 252-259

  Greiff, Warren R ^a   Morgan, William T ^a   Ponte, Jay M ^a  

^a MITRE CORPORATION   (United States)

Author keywords

Latent variables; Log linear models; Parameter estimation; Term weighting; Variance

Indexed keywords

APPROXIMATION THEORY; COMPUTER SIMULATION; FUNCTION EVALUATION; MATHEMATICAL MODELS; MATHEMATICAL TRANSFORMATIONS; PARAMETER ESTIMATION; PROBABILITY; RANDOM PROCESSES;

LOG LINEAR MODELS; PROBABILISTIC INFORMATION RETRIEVAL; RETRIEVAL STATUS VALUE;

INFORMATION RETRIEVAL;

EID: 0037481030     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/584792.584836     Document Type: Conference Paper

References (18)

1. A. Berger and J. D. Lafferty. Information retrieval as statistical translation. In SIGIR '99: Proceedings of the 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, August 15-19, 1999, Berkeley, CA, USA, pages 222-229. ACM, 1999.
2. W. S. Copper, A. Chen, and F. C. Gey. Full text retrieval based on probabilistic equations with coefficients fitted by logistic regression. In D. K. Harman, editor, The Second Text REtrieval Conference (TREC-2), pages 57-66, Gaithersburg, Md., Mar. 1994. NIST Special Publication 500-215.
3. W. S. Cooper, D. Dabney, and F. Gey. Probabilistic retrieval based on staged logistic regression. In N. Belkin, P. Ingwersen, and A. M. Mejtersen, editors, Proceedings of the 15th Annual International ACM-SIGIR Conference on Research and Development in Information Retrieval, pages 198-210, Copenhagen, Denmark, June 1992.
4. W. B. Croft and D. J. Harper. Using probabilistic models of document retrieval without relevance information. Journal of Documentation, 35(4):285-295, Dec. 1979.
5. W. A. Gale and G. Sampson. Good-turing estimation without tears. Journal of Quantitative Linguistics, 2(3):217-237, 1995.
6. F. G. Gey. Inferring probability of relevance using the method of logistic regression. In W. B. Croft and C. J. van Rijsbergen, editors. Proceedings of the 17th Annual International ACM-SIGIR Conference on Research and Development in Information Retrieval, pages 222-231, Dublin, Ireland, July 1994.
7. I. J. Good. The population of frequencies and the estimation of population parameters. Biometrica, 40:237-264, 1953.
8. D. Hiemstra. A linguistically motivated probabilistic model of information retrieval. In Proceedings of the Second European Conference on Research and Advanced Technology for Digital Libraries (ECDL 98), volume 513 of Lecture Notes in Computer Science, pages 569-584, New York, 1998. Springer Verlag.
9. D. Hiemstra and A. P. de Vries. Relating the new language models of information retrieval to the traditional retrieval models. Technical Report TR-CTIT-00-09, Centre for Telematics and Information Technology, University of Twente, May 2000.
10. D. W. Hosmer, Jr and S. Lemeshow. Applied Logistic Regression. John Wiley & Sons, New York, 1989.
11. M. E. Maron and J. L. Kuhns. On relevance, probabilistic indexing and information retrieval. Journal of the ACM, 7(3):216-243, July 1960.
12. D. R. H. Miller, T. Leek, and R. M. Schwartz. A hidden markov model information retrieval system. In SIGIR '99: Proceedings of the 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, August 15-19, 1999, Berkeley, CA, USA, pages 214-221. ACM 1999.
13. J. M. Ponte and W. B. Croft. A language modeling approach to information retrieval. In W. B. Croft, A. Moffat, C. J. van Rijsbergen, R. Wilkinson, and J. Zobel, editors, Proceedings of the 21st Annual International ACM-SIGIR Conference on Research and Development in Information Retrieval, pages 275-281, Melbourne, Australia, Aug. 1998. ACM Press.
14. S. E. Robertson. The probability ranking principle in IR. Journal of Documentation, 33:294-304, 1977.
15. S. E. Robertson and K. Sparck Jones. Relevance weighting of search terms. Journal of the American Society for Information Science, 27:129-146, 1977.
16. S. E. Robertson and S. Walker. Some simple effective approximations to the 2-Poisson model for probabilistic weighted retrieval. In W. B. Croft and C. J. van Rijsbergen, editors, Proceedings of the 17th Annual International ACM-SIGIR Conference on Research and Development in Information Retrieval, pages 232-241, Dublin, Ireland, July 1994.
17. S. E. Robertson, S. Walker, and M. M. Hancock-Beaulieu. Large test collection experiments on an operational, interactive system: OKAPI at TREC. Information Processing & Management, 31(3):345-360, 1995.
18. F. Song and W. B. Croft. A general language model for information retrieval. In Proceedings of the Eighth International Conference on Information and Knowledge Management, November 1999.