Ranking graph embedding for learning to rerank

IEEE Transactions on Neural Networks and Learning Systems

Volumn 24, Issue 8, 2013, Pages 1292-1303

  Pang, Yanwei ^a   Ji, Zhong ^a   Jing, Peiguang ^a   Li, Xuelong ^b  

^a TIANJIN UNIVERSITY   (China)

^b INSTITUTE OF GEOLOGY AND GEOPHYSICS   (China)

Author keywords

Dimensionality reduction; graph embedding; image search reranking; learning to rank

Indexed keywords

DIMENSIONALITY REDUCTION; DIMENSIONALITY REDUCTION METHOD; GENERALIZATION ABILITY; GRAPH EMBEDDINGS; IMAGE SEARCH RERANKING; LEARNING TO RANK; PRINCIPAL COMPONENTS ANALYSIS; SIMILARITY CALCULATION;

ARTIFICIAL INTELLIGENCE; COMPUTER NETWORKS;

PRINCIPAL COMPONENT ANALYSIS;

EID: 84880918462     PISSN: 2162237X     EISSN: 21622388     Source Type: Journal    
DOI: 10.1109/TNNLS.2013.2253798     Document Type: Article

References (52)

1. M. Belkin and P. Niyogi, "Laplacian eigenmaps and spectral techniques for embedding and clustering," in Advances in Neural Information Processing System, vol. 14. Cambridge, MA, USA: MIT Press, 2001, pp. 585-591.
2. W. Bian and D. Tao, "Biased discriminant Euclidean embedding for content-based image retrieval," IEEE Trans. Image Process., vol. 19, no. 2, pp. 545-554, Feb. 2010.
3. D. Cai, X. He, K. Zhou, J. Han, and H. Bao, "Locality sensitive discriminant analysis," in Proc. Int. Joint Conf. Artif. Intell., 2007, pp. 708-713.
4. Z. Cao, T. Qin, T. Liu, M. Tsai, and H. Li, "Learning to rank: From pairwise approach to listwise approach," in Proc. Int. Conf. Mach. Learn., 2007, pp. 129-136.
5. R. Duda, P. Hart, and D. Stork, Pattern Classification, 2nd ed., New York, NY, USA: Wiley, 2001.
6. L. Duan, W. Li, I. Tsang, and D. Xu, "Improving web image search by bag-based re-ranking," IEEE Trans. Image Process., vol. 20, no. 11, pp. 3280-3290, Nov. 2011.
7. D. Forsyth and J. Ponce, Computer Vision: A Modern Approach, 2nd ed. Englewood Cliffs, NJ, USA: Prentice-Hall, 2011, ch. 21.
8. N. Guan, D. Tao, Z. Luo, and B. Yuan, "Manifold regularized discriminative non-negative matrix factorization with fast gradient descent," IEEE Trans. Image Process., vol. 20, no. 7, pp. 2030-2048, Jul. 2011.
9. N. Guan, D. Tao, Z. Luo, and B. Yuan, "Non-negative patch alignment framework," IEEE Trans. Neural Netw., vol. 22, no. 8, pp. 1218-1230, Aug. 2011.
10. N. Guan, D. Tao, Z. Luo, and B. Yuan, "NeNMF: An optimal gradient method for non-negative matrix factorization," IEEE Trans. Signal Process., vol. 60, no. 6, pp. 2882-2898, Jun. 2012.
11. N. Guan, D. Tao, Z. Luo, and B. Yuan, "Online non-negative matrix factorization with robust stochastic approximation," IEEE Trans. Neural Netw. Learn. Syst., vol. 23, no. 7, pp. 1087-1099, Jul. 2012.
12. N. Guan, D. Tao, Z. Luo, and J. Shawe-Taylor, "MahNMF: Manhattan non-negative matrix factorization," J.Mach. Learn. Res., pp. 1-43, 2012.
13. B. Geng, L. Yang, C. Xu, and X. Hua, "Content-aware ranking for visual search," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., Jun. 2010, pp. 3400-3407.
14. X. He, S. Yan, Y. Hu, P. Niyogi, and H. Zhang, "Face recognition using Laplacianfaces," IEEE Trans. Pattern Anal. Mach. Intell., vol. 27, no. 3, pp. 328-340, Mar. 2005. (Pubitemid 40377326)
15. X. He, D. Cai, and J. Han, "Learning a maximum margin subspace for image retrieval," IEEE Trans. Knowl. Data Eng., vol. 20, no. 2, pp. 189-201, Feb. 2008.
16. R. Herbrich, T. Graepel, and K. Obermayer, "Large margin rank boundaries for ordinal regression," in Advances in Large Margin Classifiers. Cambridge, MA, USA: MIT Press, 2000, pp. 115-132.
17. W. Hsu, L. Kennedy, and S. Chang, "Video search reranking through random walk over document-level context graph," in Proc. ACM Int. Conf. Multimedia, 2007, pp. 971-980.
18. Y. Huang, D. Xu, and F. Nie, "Semi-supervised dimension reduction using trace ratio criterion," IEEE Trans. Neural Netw. Learn. Syst., vol. 23, no. 3, pp. 519-526, Mar. 2012.
19. Z. Ji, Y. Su, X. Qu, and Y. Pang, "Diversifying the image relevance reranking with absorbing random walk," in Proc. Int. Conf. Image Graph., 2011, pp. 981-986.
20. K. Jrvelin and J. Keklinen, "IR evaluation methods for retrieving highly relevant documents," in Proc. Annu. Int. ACM SIGIR Conf. Res. Develop. Inf. Retr., 2000, pp. 41-48.
21. N. Kwak, "Principal component analysis based on L1-norm maximization," IEEE Trans. Pattern Anal. Mach. Intell., vol. 30, no. 9, pp. 1672-1677, Sep. 2008.
22. P. Kontschieder, M. Donoser, and H. Bischof, "Beyond pairwise shape similarity analysis," in Proc. Asian Conf. Comput. Vis., 2009, pp. 655-666.
23. F. Li and P. Perona, "A Bayesian hierarchical model for learning natural scene categories," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., Jun. 2005, pp. 524-531.
24. Y. Liu, T. Mei, X. Hua, J. Tang, X. Wu, and S. Li, "Learning to video search rerank via pseudo preference feedback," in Proc. IEEE Int. Conf. Multimedia Expo, Jun.-2008, pp. 207-210.
25. T. Liu, Learning to Rank for Information Retrieval. Berlin, Germany: Springer-Verlag, 2011.
26. Y. Liu and T. Mei, "Optimizing visual search reranking via pairwise learning," IEEE Trans. Multimedia, vol. 13, no. 2, pp. 280-291, Apr. 2011.
27. Y. Pang, L. Zhang, and Z. Liu, "Neighborhood preserving projections (NPP): A novel linear dimension reduction method," in Proc. Int. Conf. Adv. Intell. Comput., 2005, pp. 117-125. (Pubitemid 41491052)
28. S. Roweis and L. Saul, "Nonlinear dimensionality reduction by locally linear embedding," Science, vol. 290, no. 22, pp. 2323-2326, 2000. (Pubitemid 32041578)
29. S. Robertson, "Overview of the okapi projects," J. Document., vol. 53, no. 1, pp. 3-7, 1997.
30. R. Sprinthall, Basic Statistical Analysis 9th ed. London, U.K.: Pearson, 2011.
31. M. Sugiyama, T. Ide, S. Nakajima, and J. Sese, "Semi-supervised local fisher discriminant analysis for dimensionality reduction," Mach. Learn., vol. 78, nos. 1-2, pp. 35-61, 2010.
32. F. Schroff, A. Criminisi, and A. Zisserman, "Harvesting image databases from the web," in Proc. IEEE Int. Conf. Comput. Vis., Oct. 2007, pp. 1-8.
33. X. Tian, D. Tao, and Y. Rui, "Sparse transfer learning for interactive video search reranking," ACM Trans. Multimedia Comput., Commun. Appl., vol. 8, no. 3, p. 26, 2012.
34. D. Tao, X. Tang, X. Li, and X. Wu, "Asymmetric bagging and random subspace for support vector machines-based relevance feedback in image retrieval," IEEE Trans. Pattern Anal. Mach. Intell., vol. 28, no. 7, pp. 1088-1099, Jun. 2006.
35. D. Tao, X. Li, and S. J. Maybank, "Negative samples analysis in relevance feedback," IEEE Trans. Knowl. Data Eng., vol. 19, no. 4, pp. 568-580, Apr. 2007.
36. J. Tang, S. Yan, R. Hong, G. Qi, and T. Chua, "Inferring semantic concepts from community-contributed images and noisy tags," in Proc. 17th ACM Int. Conf. Multimedia, 2009, pp. 223-232.
37. J. Tang, Z. Zha, D. Tao, T. Chua, "Semantic-gap oriented active learning for multi-label image annotation," IEEE Trans. Image Process., vol. 21, no. 4, pp. 2354-2360, Apr. 2012.
38. J. Teic, A. Natsev, L. Xie, and J. R. Smith, "Data modeling strategies for imbalanced learning in visual search," in Proc. IEEE Int. Conf. Multimedia Expo, Jul. 2007, pp. 1990-1993.
39. X. Tian, D. Tao, X. Hua, X. Wu, "Active reranking for web image search," IEEE Trans. Image Process., vol. 19, no. 3, pp. 805-820, Mar. 2010.
40. M. Wang, L. Yang, and X. Hua, "MSRA-MM: Bridging research and industrial societies for multimedia information retrieval," Microsoft Research Asia, Beijing, China, Tech. Rep. MSR-TR-2009-30, 2009.
41. X. Wang, K. Liu, and X. Tang, "Query-specific visual semantic spaces for web image re-ranking," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., Jun. 2011, pp. 857-864.
42. R. Wang, S. Shan, X. Chen, J. Chen, and W. Gao, "Maximal linear embedding for dimensionality reduction," IEEE Trans. Pattern Anal. Mach. Intell., vol. 33, no. 9, pp. 1776-1792, Sep. 2011.
43. M. Wang, X. Hua, J. Tang, and R. Hong, "Beyond distance measurement: Constructing neighborhood similarity for video annotation," IEEE Trans. Multimedia, vol. 11, no. 3, pp. 465-476, Apr. 2009.
44. M. Wang, X. Hua, T. Mei, R. Hong, G. Qi, Y. Song, and L. Dai, "Semisupervised kernel density estimation for video annotation," Comput. Vis. Image Understand., vol. 113, no. 3, pp. 384-396, 2009.
45. M. Wang, K. Yang, X. Hua, and H. Zhang, "Toward a relevant and diverse search of social images," IEEE Trans. Multimedia, vol. 12, no. 8, pp. 829-842, Dec. 2010.
46. S. Wei, Y. Zhao, Z. Zhu, and N. Liu, "Multimodal fusion for video search reranking," IEEE Trans. Knowl. Data Eng., vol. 22, no. 8, pp. 1191-1199, Aug. 2010.
47. B. Xie, M. Wang, and D. Tao, "Toward the optimization of normalized graph Laplacian," IEEE Trans. Neural Netw. Learn. Syst., vol. 22, no. 4, pp. 660-666, Apr. 2011.
48. T. Xia, D. Tao, T. Mei, and Y. Zhang, "Multiview spectral embedding," IEEE Trans. Syst., Man, Cybern., B, vol. 40, no. 6, pp. 1438-1446, Dec. 2010.
49. S. Yan, D. Xu, B. Zhang, H. Zhang, Q. Yang, and S. Lin, "Graph embedding and extensions: A general framework for dimensionality reduction," IEEE Trans. Pattern Anal. Mach. Intell., vol. 29, no. 1, pp. 40-51, Jan. 2007. (Pubitemid 46415944)
50. T. Yao, T. Mei, and C. Ngo, "Co-reranking by mutual reinforcement for image search," in Proc. ACM Int. Conf. Image Video Retr., 2010, pp. 34-41.
51. Y. Yang, W. Hsu, and H. Chen, "Online reranking via ordinal informative concepts for context fusion in concept detection and video search," IEEE Trans. Circuits Syst. Video Technol., vol. 19, no. 12, pp. 1880-1890, Dec. 2009.
52. L. Zhang, T. Mei, Y. Liu, D. Tao, and H. Zhou, "Visual search reranking via adaptive particle swarm optimization," Pattern Recognit., vol. 44, no. 8, pp. 1811-1820, 2011.