Click-through-based cross-view learning for image search

SIGIR 2014 - Proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval

Volumn , Issue , 2014, Pages 717-726

  Pan, Yingwei ^a   Yao, Ting ^b   Mei, Tao ^c   Li, Houqiang ^a   Ngo, Chong Wah ^b   Rui, Yong ^c  

^a UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA   (China)

^b CITY UNIVERSITY OF HONG KONG   (Hong Kong)

^c MICROSOFT RESEARCH   (United States)

Author keywords

Clickthrough data; Cross view learning; DNN image representation; Image search; Subspace learning

Indexed keywords

IMAGE ENHANCEMENT; IMAGE RETRIEVAL; LEARNING SYSTEMS; VECTORS;

CLICKTHROUGH DATA; CROSS-VIEW LEARNING; IMAGE REPRESENTATIONS; IMAGE SEARCH; SUBSPACE LEARNING;

SEARCH ENGINES;

EID: 84904538400     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2600428.2609568     Document Type: Conference Paper

References (33)

1. R. A. Baeza-Yates and A. Tiberi. Extracting semantic relations from query logs. In Proceedings of ACM Conference on Knowledge Discovery and Data Mining, 2007.
2. B. Bai, J. Weston, D. Grangier, R. Collobert, K. Sadamasa, Y. Qi, C. Cortes, and M. Mohri. Polynomial semantic indexing. In Proceedings of Advances in Neural Information Processing Systems, 2009.
3. D. Beeferman and A. L. Berger. Agglomerative clustering of a search engine query log. In Proceedings of ACM Conference on Knowledge Discovery and Data Mining, 2000.
4. C. F. Cadieu, H. Hong, D. Yamins, N. Pinto, N. J. Majaj, and J. J. DiCarlo. The neural representation benchmark and its evaluation on brain and machine. In Proceedings of International Conference on Learning Representations, 2013.
5. C. Cortes, M. Mohri, and A. Rostamizadeh. Two-stage learning kernel algorithms. In Proceedings of International Conference on Machine Learning, 2010.
6. N. Craswell and M. Szummer. Random walks on the click graph. In Proceedings of ACM Conference on Research and Development in Information Retrieval, 2007.
7. Z. Fang and Z. Zhang. Discriminative feature selection for multi-view cross-domain learning. In Proceedings of ACM Conference of Information and Knowledge Management, 2013.
8. Y. Gong, Q. Ke, M. Isard, and S. Lazebnik. A multi-view embedding space for modeling internet images, tags, and their semantics. International Journal of Computer Vision, (106):210-233, 2014.
9. D. Hardoon, S. Szedmak, and J. Shawe-Taylor. Canonical correlation analysis: An overview with application to learning methods. Neural Computation, 16(12):2639-2664, 2004.
10. X.-S. Hua, L. Yang, J. Wang, J. Wang, M. Ye, K. Wang, Y. Rui, and J. Li. Clickage: Towards bridging semantic and intent gaps via mining click logs of search engines. Proceedings of ACM International Conference on Multimedia, 2013.
11. V. Jain and M. Varma. Learning to re-rank: Query-dependent image re-ranking using click data. In Proceedings of International World Wide Web Conference, 2011.
12. T. Joachims. Optimizing search engines using clickthrough data. In Proceedings of ACM Conference on Knowledge Discovery and Data Mining, 2002.
13. T. Joachims, L. Granka, B. Pan, H. Hembrooke, F. Radlinski, and G. Gay. Evaluating the accuracy of implicit feedback from clicks and query reformulations in web search. ACM Trans. on Information Systems, 25(2), 2007.
14. M. Kloft, U. Brefeld, S. Sonnenburg, P. Laskov, K.-R. Muller, and A. Zien. Evaluating search engines by modeling the relationship between relevance and clicks. In Efficient and accurate lp-norm multiple kernel learning, 2009.
15. A. Krizhevsky, I. Sutskever, and G. E. Hinton. Imagenet classification with deep convolutional neural networks. In Proceedings of Advances in Neural Information Processing Systems, 2012.
16. A. Kumar, P. Rai, and H. Daume. Co-regularized multi-view spectral clustering. In Proceedings of Advances in Neural Information Processing Systems, 2011.
17. G. R. G. Lanckriet, N. Cristianini, P. L. Bartlett, L. E. Ghaoui, and M. I. Jordan. Learning the kernel matrix with semidefinite programming. Journal of Machine Learning Research, 5:27-72, 2004.
18. X. Li, Y.-Y. Wang, and A. Acero. Learning query intent from regularized click graphs. In Proceedings of ACM Conference on Research and Development in Information Retrieval, 2008.
19. Q. Mei, D. Zhou, and K. W. Church. Query suggestion using hitting time. In Proceedings of ACM Conference of Information and Knowledge Management, 2008.
20. T. Mei, Y. Rui, S. Li, and Q. Tian. Multimedia Search Reranking: A Literature Survey. ACM Computing Surveys, 46(3), Sept. 2014.
21. S. Melacci and M. Belkin. Laplacian support vector machines trained in the primal. Journal of Machine Learning Research, 12:1149-1184, 2011.
22. I. Muslea, S. Minton, and C. Knoblock. Active learning with multiple views. Journal of Artificial Intelligence Research, 27(1):203-233, 2006.
23. Y. Pan, T. Yao, K. Yang, H. Li, C.-W. Ngo, J. Wang, and T. Mei. Image search by graph-based label propagation with image representation from dnn. Proceedings of ACM International Conference on Multimedia, 2013.
24. B. Poblete and R. A. Baeza-Yates. Query-sets: using implicit feedback and query patterns to organize web documents. In Proceedings of International World Wide Web Conference, 2008.
25. R. Rosipal and N. Krämer. Overview and recent advances in partial least squares. Subspace, Latent Structure and Feature Selection, pages 34-51, 2006.
26. W. Sun and Y.-X. Yuan. Optimization theory and methods: nonlinear programming, volume 98. springer, 2006.
27. M. Trevisiol, L. Chiarandini, L. M. Aiello, and A. Jaimes. Image ranking based on user browsing behavior. In Proceedings of ACM Conference on Research and Development in Information Retrieval, 2012.
28. J.-R. Wen, J.-Y. Nie, and H. Zhang. Clustering user queries of a search engine. In Proceedings of International World Wide Web Conference, 2001.
29. Z. Wen and W. Yin. A feasible method for optimization with orthogonality constrains. Mathematical Programming, 142:397-434, 2013.
30. W. Wu, H. Li, and J. Xu. Learning query and document similarities from click-through bipartite graph with metadata. Proceedings of ACM Conference on Web Search and Data Mining, 2013.
31. C. Xu, D. Tao, and C. Xu. A survey on multi-view learning. CoRR abs/1304.5634, 2013.
32. T. Yao, T. Mei, C.-W. Ngo, and S. Li. Annotation for free: Video tagging by mining user search behavior. Proceedings of ACM International Conference on Multimedia, 2013.
33. S. Yu, B. Krishnapuram, R. Rosales, and R. Rao. Bayesian co-training. Journal of Machine Learning Research, pages 2649-2680, 2011.