Learning retrieval expert combinations with genetic algorithms

International Journal of Uncertainty, Fuzziness and Knowldege-Based Systems

Volumn 11, Issue 1, 2003, Pages 87-113

  Billhardt, Holger ^a   Borrajo, Daniel ^b   Maojo, Victor ^c  

^a UNIVERSIDAD REY JUAN CARLOS   (Spain)

^b UNIVERSIDAD CARLOS III DE MADRID   (Spain)

^c UNIVERSIDAD POLITÉCNICA DE MADRID   (Spain)

Author keywords

Context vector model; Data fusion; Genetic algorithms; Information retrieval

Indexed keywords

GENETIC ALGORITHMS; HEURISTIC METHODS; INDEXING (OF INFORMATION); INFORMATION RETRIEVAL; LEARNING SYSTEMS; PARAMETER ESTIMATION; QUERY LANGUAGES; SEMANTICS; SENSOR DATA FUSION; SYNTACTICS; VECTORS; WORD PROCESSING;

COMBINATION FUNCTION; CONTEXT VECTOR MODEL; DOCUMENT COLLECTION; EXPERT COMBINATIONS; LEARNING RETRIEVAL; SEMANTIC INDEXING; WORD MATCHING;

EXPERT SYSTEMS;

EID: 0037327947     PISSN: 02184885     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0218488503001965     Document Type: Article

References (33)

1. G. Salton and M. McGill, Introduction to Modern Information Retrieval (McGraw Hill, New York, 1983).
2. G. Salton, Automatic Text Processing: The Transformation, Analysis and Retrieval of Information by Computer (Addison Wesley, Reading, 1989).
3. R. Baeza-Yates and B. Ribeiro-Neto, Modern Information Retrieval (ACM Press, New York, 1999).
4. H. Billhardt, D. Borrajo and V. Maojo, "Using term co-occurrence data for document indexing and retrieval", Proc. 22nd Annual Colloquium on Information Retrieval Research (IRSG '2000), Cambridge, UK, April 2000, pp. 105-117.
5. H. Billhardt, D. Borrajo and V. Maojo, "A context vector model for information retrieval", Journal of the American Society for Information Science and Technology, 53 (2002) 236-249.
6. S. Deerwester, S. Dumais, G. Furnas, T. Landauer and R. Harshman, "Indexing by latent semantic analysis", Journal of the American Society for Information Science, 41 (1990) 391-407.
7. S. Dumais, "Latent semantic indexing (lsi): Trec-3 report", in Overview of the Third Text REtrieval Conference (TREC-3), ed. D. K. Harman (NIST Special Publication 500-225, Gaithersburg, 1995) pp. 219-230.
8. T. Hofmann, "Probabilistic latent semantic indexing", Proc. 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'99), Berkeley, CA, August 1999, pp. 50-57.
9. N. J. Belkin, C. Cool, W. B. Croft and J.P. Callan, "The effect of multiple query representations on information retrieval performance", Proc. Sixteenth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'93), Pittsburgh, PA, June 1993, pp. 339-346.
10. N. J. Belkin, P. Kantor, E.A. Fox and J.A. Shaw, "Combining the evidence of multiple query representations for information retrieval", Information Processing & Management, 31 (1995) 431-448.
11. S. Dumais, "Combing evidence for effective information filtering", Proc. AAAI Spring Symposium on Machine Learning in Information Access, Stanford, March 1996.
12. E. A. Fox and J. A. Shaw, "Combination of multiple searches", in The Second Text REtrieval Conference (TREC-2), ed. D. K. Harman (NIST Special Publication 500-215, Gaithersbug, 1994) pp. 243-252.
13. J. A. Shaw and E. A. Fox, "Combination of multiple searches", in Overview of the Third Text REtrieval Conference (TREC-3), ed. D. K. Harman (NIST Special Publication 500-225, Gaithersburg, 1995) pp. 105-108.
14. C. McCabe, A. Chowdhury, D. Grossman and O. Frieder, "A unified environment for fusion of information retrieval approaches", Proc. Eighth International Conference on Information Knowledge Management (CIKM 1999), Kansas City, November 1999, pp. 330-342.
15. C. C. Vogt, G. W. Cottrell, R. K. Belew and B. T. Bartell, "Using relevance to train a linear mixture of experts", in The Fifth Text REtrieval Conference (TREC-5), eds. E. M. Voorhees and D. K. Harman (NIST Special Publication 500-238, Gaithersburg, 1997) pp. 503-516.
16. B. T. Bartell, G. W. Cottrell and R. K. Belew, "Automatic combination of multiple ranked retrieval systems", Proc. 17th Annual International ACM-SIGIR Conference on Research and Development in Information Retrieval (SIGIR'94), Dublin, Ireland, July 1994, pp. 173-181.
17. J. Savoy, M. Ndarugendamwo and D. Vrajitoru, "Report on the trec-4 experiment: Combining probabilistic and vector-space schemes", in The Fourth Text REtrieval Conference (TREC-4), ed. D. K. Harman (NIST Special Publication 500-236, Gaithersburg, 1996) pp. 537-548.
18. C. C. Vogt and G. W. Cottrell, "Predicting the performance of linearly combined IR systems", Proc. 21st Annual International ACM-SIGIR Conference on Research and Development in Information Retrieval (SIGIR'98), Melbourne, Australia, August 1998, pp. 190-196.
19. C. C. Vogt and G. W. Cottrell, "Fusion via a linear combination of scores", Information Retrieval, 1 (1999) 151-173.
20. J. H. Lee, "Analysis of multiple evidence combination", Proc. 20th Annual International ACM-SIGIR Conference on Research and Development in Information Retrieval (SIGIR'97), Philadelphia, PA, July 1997, pp. 267-276.
21. C. C. Vogt, "How much more is better? Characterizing the effects of adding more IR systems to a combination", Proc. Sixth Conference on Content-Based Multimedia Information Access (RIAO2000), Paris, France, April 2000.
22. M. Boughanem, C. Chrisment and L. Tamine, "Genetic approach to query space exploration", Information Retrieval, 1 (1999) 175-192.
23. M. Boughanem, C. Julien, J. Mothe and C. Soule-Dupuy, "Mercure at trec8: Adhoc, web, clir and filtering tasks", in The Eighth Text REtrieval Conference (TREC-8), eds. E. M. Voorhees and D. K. Harman (NIST Special Publication 500-246, Gaithersburg, 2000) pp. 431-444.
24. H. Chen, "Machine learning for information retrieval: Neural networks, symbolic learning, and genetic algorithms", Journal of the American Society for Information Science, 46 (1995) 194-216.
25. D. H. Kraft, F. B. Petry, B. P. Buckles and T. Sadasivan, "The use of genetic programming to build queries for information retrieval", Proc. First IEEE Conference on Evolutionary Computation, IEEE World Congress on Computational Intelligence, volume 1, Orlando, FL, June 1994, pp. 468-473.
26. D. Vrajitoru, "Crossover improvement for the genetic algorithm in information retrieval", Information Processing and Management, 34 (1998) 405-415.
27. J. Yang, R. Korfhage and E. Rasmussen, "Query improvement in information retrieval using genetic algorithms - a report on the experiments of the trec project", in The First Text REtrieval Conference (TREC-1), ed. D. K. Harman (NIST Special Publication 500-207, Gaithersburg, 1993) pp. 31-58.
28. W. Fan, M. D. Gordon and P. Pathak, "Automatic generation of a matching function by genetic programming for effective information retrieval", Proc. 1999 American Conference on Information Systems (AIS AMCIS'99), Milwaukee, WI, August 1999.
29. P. Pathak, M. D. Gordon and W. Fan, "Effective information retrieval using genetic algorithms based matching function adaption", Proc. of 33rd Annual Hawaii International Conference on System Science, Maui, Hawaii, 2000.
30. B. T. Bartell, G. W. Cottrell and R. K. Belew, "Learning the optimal parameters in a ranked retrieval system using multi-query relevance feedback", Proc. Third Annual Symposium on Document Analysis and Information Retrieval (SDAIR'94), Las Vegas, 1994.
31. D. E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning (Addison-Wesley, Reading, 1989).
32. E. M. Voorhees and D. K. Harman (eds.), The Seventh Text Retrieval Conference (TREC-7) (NIST Publication 500-242, Gaithersburg, 1999).
33. M. F. Porter, "An algorithm for suffix stripping", Program, 14 (1980) 130-137.