相关反馈在基于内容的图像检索中成为提升检索效率的一项重要技术。然而，在图像检索中，高层语义与底层特征之间存在着巨大的“语义鸿沟”，传统的相关反馈技术需要多次反馈才能获得满意结果，这使得用户的检索任务既耗时且繁琐。因此，本文通过对图像检索反馈日志信息的存储及使用过程进行分析，提出一种新的基于记忆的相关反馈策略。通过原型系统实验，与传统反馈策略相比，本文提出的策略对检索效率有明显改善。

Relevance feedback has been proposed as an important technique to boost the retrieval performance in contentbased image retrieval (CBIR).However,since there exists a semantic gap between lowlevel features and high level semantic concepts in CBIR, typical relevance feedback techniques need to perform mutiple iterations of feedback for achieving satisfactory results. These procedures are timeconsuming and may make the users bored in the retrieval tasks. Therefore, this paper proposes a novel feedback strategy based on analysising the usage and storage process of the retrieval feedback historical information in contentbased image retrieval. The testing results of the prototype system show that the strategy we put forward significantly improves the efficiency of retrieval performance and performs better than typical relevance feedback strategies.