Relevance feedback algorithm based on learning from labeled and unlabeled data

Proceedings - IEEE International Conference on Multimedia and Expo

Volumn 1, Issue , 2003, Pages I433-I436

  Singh, Raghavendra ^a   Kothari, Ravi ^a  

^a IBM INDIA RESEARCH LAB   (India)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; CONTENT BASED RETRIEVAL; FEEDBACK; LEARNING ALGORITHMS;

ACTIVE LEARNING; CONTENTBASED IMAGE RETRIEVAL (CBIR) SYSTEM; IMAGE DATABASE; INTERACTIVE SEARCH; LABELED AND UNLABELED DATA; RELEVANCE FEEDBACK; TRAINING SETS; USER FEEDBACK;

SEARCH ENGINES;

EID: 84897803605     PISSN: 19457871     EISSN: 1945788X     Source Type: Conference Proceeding    
DOI: 10.1109/ICME.2003.1220947     Document Type: Conference Paper

References (15)

1. N.Vasconcelos and M. Kunt, "Content based image retreival from image databases: current solutions and future directions, " in Proc. of ICIP 2001.
2. X.S. Zhou and T.S. Huang, "Relevance feedback in image retrieval: A comprehensive review" ACM Multimedia Systems Journal, 2002.
3. Y. Wu, Q. Tia, and T.S. Huang, "Discriminant-EM algorithm and application to image retrieval, " in Proc. of IEEE CVPR, 2000.
4. A. Gammerman, V. Vapnik, and V. Vowk, "Learning by transduction, " in Proc. Uncertainly in Artifcial Intelligence, 1998.
5. A. Demiriz, K. Bennet, "Semi-supervised support vector machines, " in Proc. of NIPS, 1998.
6. K. Nigam, A. McCallum, S. Thrum, and T. Mitchell, "Text classification from labeled and unlabeled documents using EM, " in AAAI, 1999.
7. A. McCallum and K. Nigam, "Employing EM in pool-based active learning for text classifcation, " in Proc. of ICML, 1998.
8. R. Kothari and V. Jain, "Learning with a minimum amount of labeling effort, " IEEE Trans. on Nueral Networks, Submitted.
9. V. Fedrov, Theory of Optimal Experiments, Academic Press, 1972.
10. I.J Cox, M.L. Miller, TP. Minka, T.V. Papathomas, and P. N. Yianilos, "The Bayesian image retrieval system, PicHunter: Theory, implementation and psychophysical experiments, " IEEE Trans, on Image Processing, vol. 9, no. 1, pp. 20-37, 2000.
11. N. Vasconcelos and A. Lippman, "Bayesian representation and learning mechanisms for content based image retrieval, " in SPIE storage and Retrieval for Media Database 2000, 2000.
12. D. Goldberg, Genetic algorithms in search, optimization, and machine learning, Addison-Wesley, 1989.
13. H.S. Sueng, M. Opper, and H. Sompolinsky, "Query by committee, " in Proc. Computational Learning Theory, 1992.
14. J.R. Smith, "Content-based access of image and video libraries, " in Encyclopedia of Library and Information Science. 2001, Marcel Dekker, Inc. 2001.
15. A. Ceroni, M. Pelican, and D. E. Goldberg, "Convergence- Time models for the simple Genetic Algorithm with finite population, " Tech. Rep., University of Illinois at Urbana- Champaign, Illinois GA Lab. Report # 2001028, 2001.