By Yang Liu, Jian Shao (auth.), Guoping Qiu, Kin Man Lam, Hitoshi Kiya, Xiang-Yang Xue, C.-C. Jay Kuo, Michael S. Lew (eds.)

The 2010 Pacific-Rim convention on Multimedia (PCM 2010) was once held in Shanghai at Fudan collage, in the course of September 21–24, 2010. seeing that its inauguration in 2000, PCM has been held in numerous locations round the Pacific Rim, specifically Sydney (PCM 2000), Beijing (PCM 2001), Hsinchu (PCM 2002), Singapore (PCM 2003), Tokyo (PCM 2004), Jeju (PCM 2005), Zhejiang (PCM 2006), Hong Kong (PCM 2007), Tainan (PCM 2008), and Bangkok (PCM 2009). PCM is a huge annual foreign convention geared up as a discussion board for the dissemination of cutting-edge technological advances and examine leads to the fields of theoretical, experimental, and utilized multimedia research and processing. PCM 2010 featured a accomplished technical software which incorporated seventy five oral and fifty six poster displays chosen from 261 submissions from Australia, Canada, China, France, Germany, Hong Kong, India, Iran, Italy, Japan, Korea, Myanmar, Norway, Singapore, Taiwan, Thailand, the united kingdom, and america. 3 extraordinary researchers, Prof. Zhi-Hua Zhou from Nanjing college, Dr. Yong Rui from Microsoft, and Dr. Tie-Yan Liu from Microsoft examine Asia introduced 3 keynote talks to the convention. we're very thankful to the various those who helped to make this convention a s- cess. we wish to in particular thank Hong Lu for neighborhood association, Qi Zhang for dealing with the booklet of the court cases, and Cheng Jin for taking care of the c- ference site and exposure. We thank Fei Wu for organizing the specific consultation on large-scale multimedia seek within the social community settings.

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LASSO-Patternsearch algorithm with application to ophthalmology and genomic data. Statistics and its Interface 1(1), 137 (2008) 16. : Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society. Series B (Methodological) 58(1), 267–288 (1996) 17. : Simultaneous image classification and annotation (2009) 18. : Multi-label sparse coding for automatic image annotation (2009) 19. : MSRA-MM: Bridging Research and Industrial Societies for Multimedia Information Retrieval.

And Bing, relies on textual descriptions of images on the Web. The annotations of semantics in images with multiple precise tags are therefore crucial to searching favorite images for users. The image annotation is the process that an algorithm automatically translates one image into several keywords describing the semantics inside the image. Many cues, such as visual features, the textual description surrounding images and users’ preference profiles, can be conducted to boost image annotation. Given a training data set of images labeled with multiple tags, we are interested in training a model to encode the association between visual words and tags in this paper for image annotation.

Of Int. Conf. of World Wide Web, pp. 285–295 (2001) 22. : Combination of multiple searches. In: Proc. of the 2nd Text REtrieval Conference (1994) 23. : Building efficient and effective metasearch engines. ACM Comput. Surv. 34(1), 48–89 (2002) 24. : Scalable collaborative filtering using cluster-based smoothing. In: Proc. of. the 28th ACM SIGIR, pp. 114–121 (2005) 25. : Data Mining: Concepts and Techniques. Morgan Kaufmann, San Francisco (2006) 26. : Introduction to Information Retrieval. Cambridge University Press, Cambridge (2008) 27.

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