SP500207 NIST Special Publication 500-207: The First Text REtrieval Conference (TREC-1) Probabilistic Retrieval in the TIPSTER Collections: An Application of Staged Logistic Regression chapter W. Cooper F. Grey A. Chen National Institute of Standards and Technology Donna K. Harman Cooper, W. S. Inconsistencies and Misnomers in Probabilistic IR. Proceedings Fourteenth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. Chicago: 57-62. October 1991. Cooper, W. S.; Dabney, D.; Gey, E Probabilistic retrieval based on staged logistic regression. Proceedings of the Fifteenth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. Copenhagen: 198-210; June 1992. Cooper, W. S.; Ruizinga, P. The maximum entropy principle and its application to the design of probabilistic retrieval Systems. Information Technology: Research and Development, 1(2): 99-112; 1982. Fox, Edward A., Extending the Boolean and Vector Space Models of Information Retrieval with P-Norm Queries and Multiple Concept Types, Ph.D. Dissertation, Com- puter Science, Cornell University, 1983. Fuhr, N. Optimal polynomial retrieval functions based on the probability ranking principle. ACM Transactions on Information Systems 7(3): 183-204; 1989. Fuhr, N.; Buckley, C. A probabilistic learning approach for document indexing. ACM Transactions on Information Systems, 9(3): 223-248; 1991. Harper, D. J.; Van Rijsbergen, C. J. An evaluation of feedback in document retrieval using co-occurrence data. Journal of Documentation, 34(3): 189-216; 1978. Hosmer, D. W.; Lemeshow, S. Applied Logistic Regression. New York: Wiley; 1989. Kantor, P. retrieval Systems. 1984. Maximum entropy and the optimal design of automated information Information Technology: Research and Development, 3(2): 88-94; Keen, E. M. Terrn position ranking: Some new test results. Proceedings of the Fif- teenth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. Copenhagen: 66-76; June 1992. Lee, J. J.; Kantor, P. A study of probabilistic information retrieval systems in the case of inconsistent expert judgement. Journal of the American Society for Information Science, 42(3), 1990. Maron, M. E. Probabilistic Retrieval Models. In B. Dervin and M. Voigt (Eds.), Progress in Communication Sciences, Vol. V, Ablex, 1984, pp. 145-176. Maron, M. E.; Kuhns, J. L. On relevance, probabilistic indexing, and information retrieval. Journal of the Association for Computing Machinery, 7(3): 216-244; 1960. Robertson, S. E; Bovey, J. D. Statistical problems in the application ofprobabilis- tic models to information retrieval. British Library Research and Development Depart- ment, Report No.5739, November 1982. Robertson, S. E.; Sparck Jones, K. Relevance weighting of search terms. Journal of the American Society for Information Science, 27(3): 129-146; 1976. van Rijsbergen, C. J. A theoretical basis for the use of co-occurrence data in infor- mation retrieval. Journal ofDocumentation, 33(2): 106-119; 1977. 87