Recently more and more researchers are realizing both the challenges and the opportunities for multimedia research brought by the Internet. In order to bring together high-quality and novel research works on Internet Multimedia Mining, Xian-Sheng Hua, Zhi-Hua Zhou, and myself are organizing a workshop on the topic at the forthcoming IEEE International Conference on Data Mining. One of the major obstacles of Internet Multimedia Mining research is the difficulty in forming a good dataset for algorithm developing, system prototyping and performance evaluation. Together with this workshop, we release a benchmark dataset, which is based on real Internet multimedia data and real Internet multimedia search engines (check the website for details). Submissions to this workshop are encouraged to use this dataset, but papers/demos working on other Internet-based datasets are also welcome. The deadline for submitting a maximum of 10 pages in the IEEE 2-column format is August 8.
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Although the Mexican flu can still influence the final conference dates, the forhtcoming paper for ICME 2009 in Cancun by Arjan Setz and myself, entitled “Can Social Tagged Images Aid Concept-Based Video Search?” is available online now. This paper seeks to unravel whether commonly available social tagged images can be exploited as a training resource for concept-based video search. Since social tags are known to be ambiguous, overly personalized, and often error prone, we place special emphasis on the role of disambiguation. We present a systematic experimental study that evaluates concept detectors based on social tagged images, and their disambiguated versions, in three application scenarios: within-domain, cross-domain, and together with an interacting user. The results indicate that social tagged images can aid concept-based video search indeed, especially after disambiguation and when used in an interactive video retrieval setting. These results open-up interesting avenues for future research.

