Learning to rank

Information Retrieval

Volumn 8, Issue 3, 2005, Pages 359-381

  Trotman, Andrew ^a  

^a UNIVERSITY OF OTAGO   (New Zealand)

Author keywords

Genetic programming; Machine learning; Searching; Socument ranking

Indexed keywords

EID: 17444418317     PISSN: 13864564     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10791-005-6991-7     Document Type: Article

References (40)

1. Anh VN and Moffat A (2002) Improved retrieval effectiveness through impact transformation. Australian Computer Science Communications, 24(2):41-47.
2. Buckley C (1991) trec_eval. Available: ftp.cs.cornell.edu/pub/smart.
3. Buckley C and Voorhees EM (2000) Evaluating evaluation measure stability. In: Proceedings of the 23rd ACM SIGIR Conference on Information Retrieval, pp. 33-40.
4. Clarke CLA, Cormack GV and Tudhope EA (2000) Relevance ranking for one to three term queries. Information Processing and Management, 36(2):291-311.
5. De Jong KA (1975) An analysis of the behavior of a class of genetic adaptive systems. Unpublished Ph.D., University of Michigan.
6. Fan W, Gordon MD and Pathak P (1999) Automatic generation of a matching function by genetic programming for effective information retrieval. In: Proceedings of the 1999 American Conference on Information Systems.
7. Fan W, Gordon MD and Pathak P (2004) A generic ranking function discovery framework by genetic programming for information retrieval. Information Processing and Management, 40(4):587-602.
8. Fan W, Gordon MD, Pathak P, Xi W and Fox EA (2004) Ranking function optimization for effective web search by genetic programming: An empirical study. In: Proceedings of the 37th Annual Hawaii International Conference on System Sciences.
9. Grefenstette JJ (1986) Optimization of control parameters for genetic algorithms. IEEE Transactions on Systems, Man, and Cybernetics, 16(1):122-128.
10. Harman D (1992) Ranking algorithms. In: Frakes WB and Baeza-Yates R. Eds., Information retrieval: Data Structures and Algorithms Englewood Cliffs, New Jersey, USA, Prentice Hall, PP. 363-392.
11. Harman D (1993) Overview of the first TREC conference. In: Proceedings of the 16th ACM SIGIR Conference on Information Retrieval, pp. 36-47.
12. Hart WE and Belew RK (1996) Optimization with genetic algorithm hybrids that use local searches. In: Belew, R.K. and Mitchell M. Eds. Adaptive Individuals in evolving Populations: Models and Algorithms Addison-Wesley Longman Publishing Co., Inc. pp. 483-496.
13. Hawking D, Craswell N, Thistlewaite P and Harman D (1999) Results and challenges in web search evaluation. In: Proceedings of the 8th International Conference on World Wide Web, pp. 1321-1330.
14. Holland JH (1975). Adaptation in Natural and Artificial Systems. Ann Arbor, University of Michigan Press.
15. Igel C and Chellapilla K (1999) Investigating the influence of depth and degree of genotypic change on fitness in genetic programming. In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO '99), pp. 1061-1068.
16. Kaszkiel M and Zobel J (1998) Term-ordered query evaluation versus document-ordered query evaluation for large document databases. In: Proceedings of the 21st ACM SIGIR Conference on Information Retrieval, pp. 343-344.
17. Kekäläinen J and Järvelin K (2002) Using graded relevance assessments in IR evaluation. Journal of the American Society for Information Science and Technology, 53(13):1120-1129.
18. Khuri S, Bäck T and Heitkötter J (1994) An evolutionary approach to combinatorial optimization problems. In: Proceedings of the 22nd Annual ACM Computer Science Conference, pp. 66-73.
19. Kleinberg JM (1999) Authoritative sources in a hyperlinked environment. Journal of the ACM, 46(5):604-632.
20. Koza JR (1992) Genetic Programming: On the Programming of Computers by Means of Natural Selection. MIT Press, Cambridge, MA, USA.
21. Oren N (2002a) Improving the effectiveness of information retrieval with genetic programming. Unpublished M.Sc., University of the Witwatersrand, Johannesburg.
22. Oren N (2002b) Reexamining tf.idf based information retrieval with genetic programming. In: Proceedings of the 2002 Annual Research Conference of the South African Institute of Computer Scientists and Information Technologists on Enablement through Technology (SAICSIT), pp. 224-234.
23. Page L, Brin S, Motwani R, and Winograd T (1998) The PageRank Citation Ranking: Bringing Order to the Web (1999-66), Stanford Digital Library Technologies Project.
24. Possas B, Ziviani N, Meira W, and Ribeiro-Neto B (2002) Set-based model: A new approach for information retrieval. In: Proceedings of the 25th ACM SIGIR Conference on Information Retrieval, pp. 230-237.
25. Raghavan VV, Shi H-p, and Yu CT (1983) Evaluation of the 2-Poisson model as a basis for using term frequency data in searching. In Proceedings of the 6th ACM SIGIR Conference on Information Retrieval, pp. 88-100.
26. Robertson SE and Sparck Jones K (1976) Relevance weighting of search terms. Journal of the American Society for Information Science, 27(3): 129-146.
27. Sparck Jones, Robertson SE and Walker S (1999) Okapi/Keenbow at TREC-8. In: Proceedings of the 8th Text REtrieval Conference (TREC-8).
28. Robertson SE, Walker S, Beaulieu MM, Gatford M, and Payne A (1995) Okapi at TREC-4. In: Proceedings of the 4th Text REtrieval Conference (TREC-4), pp. 73-96.
29. Robertson SE, Walker S, Jones S, Beaulieu MM, and Gatford M (1994) Okapi at TREC-3. In Proceedings of the 3rd Text REtrieval Conference (TREC-3), pp. 109-126.
30. Salton G and Buckley C (1988) Term weighting approaches in automatic text retrieval. Information Processing and Management, 24(5):513-523.
31. Salton G, Wong A, and Yang CS (1975) A vector space model for automatic indexing. Communications of the ACM, 18(11):613-620.
32. Savoy J, Ndarugendamwo M, and Vrajitoru D (1995) Report on the TREC-4 experiment: Combining probabilistic and vector-space schemes. In: Proceedings of the 4th Text REtrieval Conference (TREC-4), pp. 537-547.
33. Shaw WM, Wood JB, Wood RE, and Tibbo HR (1991) The cystic fibrosis database: Content and research opportunities. Library and Information Science Research, 13: 347-366.
34. Smart W and Zhang M (2004) Applying online gradient-descent search to genetic programming for object recognition. In: Proceedings of the 2nd Workshop on Australasian Information Security, Data Mining and Web Intelligence, and Software Internationalisation.
35. Tongchim S and Chongstitvatana P (2000) Comparison between synchronous and asynchronous implementation of parallel genetic programming. In: Proceedings of the 5th International Symposium on Artificial Life and Robotics (AROB), pp. 251-254.
36. Williams HE and Zobel J (1999) Compressing integers for fast file access. Computer Journal 42(3): 193-201.
37. Witten IH, Moffat A, and Bell TC (1994) Managing Gigabytes: Compressing and Indexing Documents and Images. Van Nostrand Reinhold, New York, USA.
38. Zobel J and Moffat A (1995) Adding compression to a full-text retrieval system. Software-Practice and Experience, 25(8):891-903.
39. Zobel J and Moffat A (1998) Exploring the similarity space. SIGIR Forum, 32(1): 18-34.
40. Zobel J, Moffat A, and Ramamohanarao K (1998) Inverted files versus signature files for text indexing. Transactions on Database Systems, 23(4):453-490.