Learning to rank for web image retrieval based on genetic programming

Aus de_evolutionary_art_org
Wechseln zu: Navigation, Suche


Piji Li and Jun Ma: Learning to rank for web image retrieval based on genetic programming. 2nd IEEE International Conference on Broadband Network Multimedia Technology, IC-BNMT '09, pp. 137-142, October 2009.




Ranking is a crucial task in information retrieval systems. This paper proposes a novel ranking model named WIRank, which employs a layered genetic programming architecture to automatically generate an effective ranking function, by combining various types of evidences in Web image retrieval, including text information, image-based features and link structure analysis. This paper also introduces a new significant feature to represent images: Temporal information, which is rarely utilized in the current information retrieval systems and applications. The experimental results show that the proposed algorithms are capable of learning effective ranking functions for Web image retrieval. Significant improvement in relevancy obtained, in comparison to some other well-known ranking techniques, in terms of MAP, NDCG@n and D@n.

Extended Abstract


Used References

Z. Cao, T. Qin, T. Liu, M. Tsai, and H. Li. Learning to rank: from pairwise approach to listwise approach. In Proceedings of the 24th international conference on Machine learning, pages 129-136. ACM New York, NY, USA, 2007. http://dx.doi.org/10.1145/1273496.1273513

Y. Hu, M. Li, and N. Yu. Multiple-instance ranking: Learning to rank images for image retrieval. In IEEE Conference on Computer Vision and Pattern Recognition(CVPR), pages 1-8, 2008. http://dx.doi.org/10.1109/CVPR.2008.4587541

J. Yeh, J. Lin, H. Ke, and W. Yang. Learning to rank for information retrieval using genetic programming. In LR4IR, 2007.

R. Baeza-Yates, B. Ribeiro-Neto, et al. Modern information retrieval. Addison-Wesley Harlow, England, 1999.

R. Torres, A. Falc̃ao, M. Gonçalves, J. Papa, B. Zhang,W. Fan, and E. Fox. A genetic programming frameworkfor content-based image retrieval. Pattern Recognition,42(2):283-292, 2009. http://dx.doi.org/10.1016/j.patcog.2008.04.010

Y. Jing and S. Baluja. VisualRank: Applying PageRank to Large-Scale Image Search. IEEE Transactions on Pattern Analysis and Machine Intelligence, 30(11):1877-1890, 2008. http://dx.doi.org/10.1109/TPAMI.2008.121

L. Page, S. Brin, R. Motwani, and T. Winograd. The pagerank citation ranking: Bringing order to the web. 1998.

J. Kleinberg. Authoritative sources in a hyperlinked environment. Journal of the ACM, 46(5):604-632, 1999. http://dx.doi.org/10.1145/324133.324140

X. He, D. Cai, J. Wen, W. Ma, and H. Zhang. ImageSeer: Clustering and Searching WWW Images Using Link and Page Layout Analysis. Technical report, Microsoft Technical Report.

K. Järvelin and J. Kekäläinen. Cumulated gain-based evaluation of IR techniques. ACM Transactions on Information Systems (TOIS), 20(4):422-446, 2002. http://dx.doi.org/10.1145/582415.582418


Full Text

[extern file]

intern file

Sonstige Links