A formal study of information retrieval heuristics

Proceedings of Sheffield SIGIR - Twenty-Seventh Annual International ACM SIGIR Conference on Research and Development in Information Retrieval

Volumn , Issue , 2004, Pages 49-56

  Fang, Hui ^a   Tao, Tao ^a   Zhai, ChengXiang ^a  

^a University of Illinois at Urbana Champaign   (United States)

Author keywords

Constraints; Formal models; Retrieval heuristics; TF IDF weighting

Indexed keywords

CONSTRAINT THEORY; ENGINEERING RESEARCH; HEURISTIC METHODS; MATHEMATICAL MODELS; PARAMETER ESTIMATION; VECTORS;

FORMAL MODELS; INFORMATION SEARCH; RETRIEVAL MODELS; VECTOR SPACE MODELS;

INFORMATION RETRIEVAL;

EID: 8644248346     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1008992.1009004     Document Type: Conference Paper

References (21)

1. G. Amati and C. J. V. Rijsbergen. Probabilistic models of information retrieval based on measuring the divergence from randomness. ACM Transactions on Information Systems, 20(4):357-389, 2002.
2. N. Fuhr. Language models and uncertain inference in information retrieval. In Proceedings of the Language Modeling and IR workshop.
3. N. Fuhr. Probabilistic models in information retrieval. The Computer Journal, 35(3):243-255, 1992.
4. J. Kleinberg. An impossibility theorem for clustering. In Advances in NIPS 15, 2002.
5. J. Lafferty and C. Zhai. Probabilistic relevance models based on document and query generation. In W. B. Croft and J. Lafferty, editors, Language Modeling and Information Retrieval. Kluwer Academic Publishers, 2003.
6. J. Ponte and W. B. Croft. A language modeling approach to information retrieval. In Proceedings of the ACM SIGIR'98, pages 275-281, 1998.
7. S. Robertson and K. Sparck Jones. Relevance weighting of search terms. Journal of the American Society for Information Science, 27:129-146, 1976.
8. S. Robertson and S. Walker. Some simple effective approximations to the 2-poisson model for probabilistic weighted retrieval. In Proceedings of SIGIR'94, pages 232-241, 1994.
9. S. Robertson and S. Walker. On relevance weights with little relevance information. In Proceedings of SIGIR'97, pages 16-24, 1997.
10. G. Salton. Automatic Text Processing: The Transformation, Analysis and Retrieval of Information by Computer. Addison-Wesley, 1989.
11. G. Salton and C. Buckley. Term-weighting approaches in automatic text retrieval. Information Processing and Management, 24:513-523, 1988.
12. G. Salton and M. McGill. Introduction to Modern Information Retrieval. McGraw-Hill, 1983.
13. G. Salton, C. S. Yang, and C. T. Yu. A theory of term importance in automatic text analysis. Journal of the American Society for Information Science, 26(1):33-44, Jan-Feb 1975.
14. A. Singhal. Modern information retrieval: A brief overview. Bulletin of the IEEE Computer Society Technical Committee on Data Engineering, 24(4):35-43, 2001.
15. H. Turtle and W. B. Croft. Evaluation of an inference network-based retrieval model. ACM Transactions on Information Systems, 9(3):187-222, 1991.
16. C. J. van Rijbergen. A theoretical basis for theuse of co-occurrence data in information retrieval. Journal of Documentation, pages 106-119, 1977.
17. C. J. van Rijsbergen. A non-classical logic for information retrieval. The Computer Journal, 29(6), 1986.
18. E. Voorhees and D. Harman, editors. Proceedings of Text REtrieval Conference (TREC1-9). NIST Special Publications, 2001. http://trec.nist.gov/ pubs.html.
19. S. K. M. Wong and Y. Y. Yao. On modeling information retrieval with probabilistic inference. ACM Transactions on Information Systems, 13(1):69-99, 1995.
20. C. Zhai and J. Lafferty. A study of smoothing methods for language models applied to ad hoc information retrieval. In Proceedings of SIGIR'01, pages 334-342, Sept 2001.
21. J. Zobel and A. Moffat. Exploring the similarity space. SIGIR Forum, 31(1):18-34, 1998.