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Formalism of Content-based Multimedia Systems

Part of the The Information Retrieval Series book series (INRE, volume 9)

2.7 Conclusions

In this chapter, a new formalism for content-based retrieval multimedia systems is proposed to provide a generic framework and criterion for describing and evaluating content-based retrieval applications. In particular, we have proposed novel methods to customize the similarity-based retrieval engine via learning based on ranking feedback from users. From our preliminary experimental results in face retrieval, the system is able to adapt its similarity function to improve on subsequent retrievals, in both short-term and long-term senses. While the perceptual consistency in similarity matching of a single user can be captured by our long-term learning approach as suggested by the experimental results and thus can be exploited to build personalized multimedia search engine, it is still uncertain that the same perceptual consistency can be extended to multiple users.

Keywords

Mean Square Error Feature Measure Pattern Classification Query Object Similarity Match 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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© Kluwer Academic Publishers 2002

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