A Long-Term Learning-Based Dynamic User Model in Image Retrieval
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    Abstract:

    This paper proposes a probabilistic model incorporating long-term learning to estimate a dynamic user model. By using RF sequence as the user pattern, the approach can gradually update the prediction of current user based on matching the current user pattern with the user patterns in log. Compared with the invariant user model in PicHunter, the model is capable of dynamically adjusting when more user actions are observed, thus provides more accurate prediction for probability distribution. Experimental results on 11 000 images show that this approach can improve the retrieval accuracy apparently.

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张亮,周向东,张琪,施伯乐.图像检索中基于长期学习的动态用户模型.软件学报,2005,16(2):233-238

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  • Received:July 25,2003
  • Revised:September 08,2004
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