Estimation of statistical translation models based on mutual information for ad hoc information retrieval

SIGIR 2010 Proceedings - 33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval

Volumn , Issue , 2010, Pages 323-330

  Karimzadehgan, Maryam ^a   Zhai, ChengXiang ^a  

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

Author keywords

Estimation; Feedback; Language models; Smoothing; Statistical machine translation

Indexed keywords

DOCUMENT COLLECTION; DOCUMENT LANGUAGE MODELS; ESTIMATION METHODS; EXACT MATCHING; LANGUAGE MODEL; MUTUAL INFORMATIONS; NORMALIZED MUTUAL INFORMATION; PSEUDO RELEVANCE FEEDBACK; QUERY METHODS; QUERY WORDS; QUERY-BASED; REGULARIZATION STRATEGIES; RETRIEVAL ACCURACY; SEMANTIC RELATIONS; SMOOTHING; STATISTICAL MACHINE TRANSLATION; STATISTICAL TRANSLATION MODEL; TRAINING DATA; TRANSLATION MODELS;

COMPUTATIONAL LINGUISTICS; ESTIMATION; FEEDBACK; INFORMATION THEORY; NATURAL LANGUAGE PROCESSING SYSTEMS; PROBABILITY; PROBABILITY DENSITY FUNCTION; SPEECH TRANSMISSION; TRANSLATION (LANGUAGES);

INFORMATION RETRIEVAL;

EID: 77956032016     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1835449.1835505     Document Type: Conference Paper

References (42)

1. J. Bai, D. Song, P. Bruza, J. Y. Nie, and G. Cao. Query expansion using term relationships in language models for information retrieval. ACM CIKM, pages 688-695, 2005.
2. A. Berger and J. Lafferty. Information retrieval as statistical translation. ACM SIGIR, pages 222-229, 1999.
3. P. Brown, S. A. D. Pietra, V. J. D. Pietra, and R. Mercer. The mathematics of statistical machine translation: Parameter estimation. Computational Linguistics, 19(2):263-311, 1993.
4. G. Cao, J. Y. Nie, and J. Bai. Integrating word relationships into language models. ACM SIGIR, pages 298-305, 2005.
5. A. P. Dempster, N. M. Laird, and D. B. Rubin. Maximum likelihood from incomplete data via the em algorithm. ACM SIGKDD, 39(B):1-38, 1997.
6. N. Fuhr. Probabilistic models in information retrieval. The Computer Journal, 35(3):243-255, 1992.
7. F. Jelinek. Statistical Methods for speech recognition. MIT Press., 1997.
8. R. Jin, A. G. Hauptmann, and C. X. Zhai. Title language model for information retrieval. In ACM SIGIR, pages 42-48, 2002.
9. Y. Jing and B. Croft. An association thesaurus for information retrieval. RIAO, pages 141-160, 1994.
10. O. Kurland and L. Lee. Corpus structure, language models, and ad hoc information retrieval. ACM SIGIR, pages 194-201, 2004.
11. J. Lafferty and C. Zhai. Document language models, query models and risk minimization for information retrieval. ACM SIGIR, pages 111-119, 2001.
12. V. Lavrenko, M. Choquette, and B. Croft. Cross-lingual relevance models. ACM SIGIR, pages 175-182, 2002.
13. V. Lavrenko and B. Croft. Relevance-based language models. ACM SIGIR, pages 120-127, 2001.
14. M. Lesk and B. Croft. Word-word associations in document retrieval systems. American Documentation, 20:20-27, 1969.
15. S. Liu, F. Lin, C. Yu, and W. Meng. An effective approach to document retrieval via utilizing wordnet and recognizing phrases. ACM SIGIR, pages 266-272, 2004.
16. X. Liu and W. B. Croft. Cluster-based retrieval using language models. In ACM SIGIR, pages 186-193, 2004.
17. R. Mandala, T. tokunaga, H. Tanaka, and K. Satoh. Ad hoc retrieval experiments using wordnet and automatically constructed thesauri. TREC-7, pages 475-481, 1998.
18. D. Metzler, Y. Bernstein, B. Croft, A. Moffat, and J. Zobel. Similarity measures for tracking information flow. ACM CIKM, pages 517-524, 2005.
19. V. Murdock and B. Croft. Simple translation models for sentence retrieval in factoid question answering. ACM SIGIR, pages 31-35, 2004.
20. J.-Y. Nie, M. Simard, P. Isabelle, and R. Durand. Cross-language information retrieval based on parallel texts and automatic mining of parallel texts from the web. In ACM SIGIR, pages 74-81, 1999.
21. H. J. Peat and P. Willett. The limitations of term co-occurrence data for query expansion in document retrieval systems. J. of Information science, 42(5):378-383, 1991.
22. J. Ponte and W. B. Croft. A language modeling approach to information retrieval. ACM SIGIR, pages 275-281, 1998.
23. M. Porter. An algorithm for suffix stripping. Program, 14(3), 1980.
24. Y. Qiu and H. Frei. Concept based query expansion. ACM SIGIR, pages 160-169, 1993.
25. C. J. V. Rijbergen. A theoretical basis for the use of co-occurrence data in information retrieval. Journal of Documentation, pages 106-119, 1977.
26. C. J. V. Rijsbergen. Information retrieval. Butterworths, 1979.
27. S. Robertson and K. Sparck. Relevance weighting of search terms. Journal of American Society for Information Science, 27:129-146, 1976.
28. G. Salton. Automatic Text Processing: The Transformation, Analysis and Retrieval of Information by Computer. Addison-Wesley, 1989.
29. G. Salton and M. McGill. Introduction to Modern Information Retrieval. McGraw-Hill., 1983.
30. G. Salton, C. S. Yang, and C. T. Yu. A theory of term importance in automatic text analysis. Journal of American Society for Information Science, 26(1):33-44, 1975.
31. H. Schutze and J. O. Pedersen. A co-occurrence based thesaurus and two applications to information retrieval. Information and processing management, 33(3):307-318, 1997.
32. A. F. Smeaton and C. J. V. Rijsbergen. The retrieval effects of query expansion on a feedback document retrieval system. The Computer Journal, 26(3):239-246, 1983.
33. T. Tao, X. Wang, Q. Mei, and C. Zhai. Language model information retrieval with document expansion. In HLT-NAACL, pages 407-414, 2006.
34. H. Turtle and W. B. Croft. Evaluation of an inference network-based retrieval model. ACM Transactions on Information Systems, 9(3):187-222, 1991.
35. E. M. Voorhess. Query expansion using lexical-semantic relations. ACM SIGIR, pages 61-69, 1994.
36. X. Wei and W. B. Croft. Lda-based document models for ad-hoc retrieval. In ACM SIGIR, pages 178-185, 2006.
37. F. Wilcoxon. Individual comparisons by ranking methods. Biometrics, 1:80-83, 1945.
38. J. Xu and B. Croft. Query expansion using local and global document analysis. ACM SIGIR, pages 4-11, 1996.
39. J. Xu, R. Weischedel, and C. Nguyen. Evaluating a probabilistic model for cross-lingual information retrieval. ACM SIGIR, pages 105-110, 2001.
40. X. Xue, J. Jeon, and W. B. Croft. Retrieval models for question and answer archives. In ACM SIGIR, pages 475-482, 2008.
41. C. Zhai and J. Lafferty. Model-based feedback in the language modeling approach to information retrieval. ACM CIKM, pages 403-410, 2001.
42. C. Zhai and J. Lafferty. A study of smoothing methods for language models applied to ad hoc information retrieval. ACM SIGIR, pages 334-342, 2001.