Social media sharing websites like flickr shares images using their respective tags. According to this tag, images can be retrieved and this process is known as tag-based image retrieval. However, making the tagged images as top ranked result relevant is challenging. In this paper, we propose a social re-grading system for tag-based image search with the consideration of image retrieval and diversity. Images are re-graded according to their visual information, semantic information, and social clues. The initial results include images contributed by different social users. Usually each user contributes multiple images by their views. First, we sort these images by inter- user re-grading and intra-user re-grading. Each userís contributed image come higher position and thus images are stored in social image dataset in the database to sort images and it is also re-graded by tag-based image search. Experimental results on a flickr dataset show that our social re-grading method is effective and efficient.
J. Senthil Murugan, T. Sathish Prabhu, R. Malarvizhi
Image Search, Re-Grading, Image Retrieval, Social Input, Social Media
- D. Liu, X. Hua, L. Yang, M.Wang, and H. Zhang, "Tag ranking,"in Proc.Int. Conf. World Wide Web, 2009, pp. 351–360.
- X. Li, C. Snoek, and M. Worring, "Learning tag relevance by neighbor voting for social image retrieval," in Proc. ACM Int. Conf. Multimedia Inform. Retrieval, 2008, pp. 180–187.
- K. Yang, M. Wang, X. Hua, and H. Zhang, "Social image search with diverse relevance ranking," in Proc. Int. Conf. Magn. Magn. Mater., 2010, pp. 174–184.
- M. Wang, K. Yang, X. Hua, and H. Zhang, "Towards relevant and diverse search of social images," IEEE Trans.Multimedia, vol. 12, no. 8, pp. 829–842, Dec. 2010.
- A. Ksibi, A. B. Ammar, and C. B. Amar, "Adaptive diversification for tag-based social image retrieval," Int. J. Multimedia Inform. Retrieval, vol. 3, no. 1, pp. 29–39, 2014.
- D. Cai, X. He, Z. Li, W. Ma, and J. Wen, "Hierarchical clustering of WWW image search results using visual, textual and link information, presented at the ACM Multimedia Conf., New York, NY, USA, 2004.
- R. Leuken, L. Garcia, X. Olivares, and R. Zwol, "Visual diversification of image search results," in Proc. 18th Int. Conf. World Wide Web, 2009, pp. 341–350.
- R. Cilibrasi and P. Vitanyi, "The Google similarity distance," IEEE Trans.Knowl. Data Eng., vol. 19, no. 3, pp. 1065–1076, Mar. 2007.
- G. Agrawal and R Chaudhary, "Relevancy tag ranking," in Proc. IEEE 2nd Int. Conf. Comput. Commun. Technol., Sep. 2011, pp. 169–173.
- L. Wu and R. Jin, "Tag completion for image retrieval," IEEE Trans. Pattern Anal. Mach. Intell., vol. 35, no. 3, pp. 716–727, Mar. 2013.
- Y. Yang, Y. Gao, H. Zhang, and J. Shao, "Image tagging with social assistance," in Proc. Int. Conf. Multimedia Retrieval, 2014, Art. no. 81.
- S. Lee, W. D. Neve, and Y. M. Ro, "Visually weighted neighbor voting for image tag relevance learning," Multimedia Tools Appl., vol. 72, no. 2, pp. 1363–1386, 2013.
- X. Li, "Tag relevance fusion for social image retrieval," Multimedia Syst., pp. 1–12, 2014.
- D. Mishra, U. P. Singh, and V. Richhariya, "Tag relevance for social image retrieval in accordance with neighbor voting algorithm," Int. J. Comput.Sci. Netw. Secur., vol. 14, no. 7, pp. 50–57, 2014.
- F. Sun, M. Wang, and D. Wang, "Optimizing social image search with multiple criteria: Relevance, diversity, and typicality," Neurocomputing, vol. 95, pp. 40–47, 2012.
- B. Wang, Z. Li, and M. Li., "Large-scale duplicate detection for web image search," in Proc. IEEE Int. Conf. Multimedia Expo., Jul. 2006, pp. 353–356.
- A. Ksibi, G. Feki, A. B. Ammar, and C. B. Amar, "Effective diversification for ambiguous queries in social image retrieval," in Computer Analysis of Images and Patterns. Berlin, Germany: Springer, 2013, pp. 571– 578.
- X. Zhu and W. Nejdl, "An adaptive teleportation random walk model for learning social tag relevance," in Proc. 37th Int. ACM SIGIR Conf. Res. Develop. Inform. Retrieval, 2014, pp. 223–232.
- A. Sun and S. Bhowmick, "Image tag clarity: In search of visual representative tags for social images," in Proc. 1st SIGMM Workshop Social Media, 2009, pp. 19–26.
- X. Qian, X. Hua, Y. Tang, and T. Mei, "Social image tagging with diverse semantics," IEEE Trans. Cybern., vol. 44, no. 12, pp. 2493–2508, Dec.2014.
- Y. Gu, X. Qian, and Q. Li., "Image annotation by latent community detection and multikernel learning," IEEE Trans. Image Process., vol. 24, no. 11, pp. 3450–3463, Nov. 2015.
- G.-J. Qi, C. C. Aggarwal, J. Han, and T. Huang, "Mining collective intelligence in diverse groups," in Proc. 22nd Int. Conf. World Wide Web, 2013, pp. 1041–1052.
- A. Krizhevsky, I. Sutskever, and G. E. Hinton, "ImageNet classification with deep convolutional neural networks," in Proc. Adv. Neural Inform. Process. Syst. 25, 2012, pp. 1106–1114.
|Published in :
||Volume 3 | Issue 1 | January-February - 2017
|Date of Publication
Cite This Article
J. Senthil Murugan, T. Sathish Prabhu, R. Malarvizhi, "Exploration of Ticket/Label Based Representation by Social Re-Grading", International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 3, Issue 1, pp.549-555, January-February-2017.
URL : http://ijsrset.com/IJSRSET1731137.php