Relevance feedback document retrieval using Support Vector Machines

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3430 LNAI, Issue , 2005, Pages 59-73

  Onoda, Takashi ^a   Murata, Hiroshi ^a   Yamada, Seiji ^b  

^a CENTRAL RESEARCH INSTITUTE OF ELECTRIC POWER INDUSTRY   (Japan)

^b NATIONAL INSTITUTE OF INFORMATICS   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

DATA MINING; EVALUATION; FEEDBACK; ITERATIVE METHODS; LEARNING SYSTEMS; MATHEMATICAL MODELS;

DOCUMENT RETRIEVAL; HUMAN TESTING; SUPPORT VECTOR MACHINE;

INFORMATION RETRIEVAL SYSTEMS;

EID: 26844554964     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11423270_4     Document Type: Conference Paper

References (19)

1. Yates, R.B., Neto, B.R.: Modern Information Retrieval. Addison Wesley (1999)
2. TREC: (http://trec.nist.gov/)
3. IREX: (http://cs.nyu.edu/cs/projects/proteus/irex/)
4. NTCIR: (http://www.rd.nacsis.ac.jp/ntcadm/)
5. Salton, G., McGill, J.: Introduction to modern information retrieval. McGraw-Hill (1983)
6. Salton, G., ed. In: Relevance feedback in information retrieval. Englewood Cliffs, N.J.: Prentice Hall (1971) 313-323
7. Okabe, M., Yamada, S.: Interactive document retrieval with relational learning. In: Proceedings of the 16th ACM Symposium on Applied Computing. (2001) 27-211
8. Tong, S., Koller, D.: Support vector machine active learning with applications to text classification. In: Journal of Machine Learning Research. Volume 2. (2001) 45-66
9. Drucker, H., Shahrary, B., Gibbon, D.C.: Relevance feedback using support vector machines. In: Proceedings of the Eighteenth International Conference on Machine Learning. (2001) 122-129
10. Onoda, T., Murata, H., Yamada, S.: Interactive document retrieval with active learning. In: International Workshop on Active Mining (AM-2002), Maebashi, Japan (2002) 126-131
11. Vapnik, V.: The Nature of Statistical Learning Theory. Springer (1995)
12. Bishop, C.: Neural Networks for Pattern Recognition. Clarendon Press, Oxford (1995)
13. Murata, N., Yoshizawa, S., Amari, S.: Network information criterion - determining the number of hidden units for an artificial neural network model. IEEE Transactions on Neural Networks 5 (1994) 865-872
14. Onoda, T.: Neural network information criterion for the optimal number of hidden units. In: Proc. ICNN'95. (1995) 275-280
15. Orr, J., Müller, K.R., eds.: Neural Networks: Tricks of the Trade. LNCS 1524, Springer Verlag (1998)
16. Boser, B., Guyon, I., Vapnik, V.: A training algorithm for optimal margin classifiers. In Haussler, D., ed.: 5th Annual ACM Workshop on COLT, Pittsburgh, PA, ACM Press (1992) 144-152
17. Schölkopf, B., Smola, A., Williamson, R., Bartlett, P.: New support vector algorithms. Neural Computaion 12 (2000) 1083-1121
18. Schapire, R., Singer, Y., Singhal, A.: Boosting and rocchio applied to text filtering. In: Proceedings of the Twenty-First Annual International ACM SIGIR. (1998) 215-223
19. Kernel-Machines: (http://www.kernel-machines.org/)