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首页> 外文期刊>Journal of Zhejiang University. Science >Web multimedia information retrieval using improved Bayesian algorithm
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Web multimedia information retrieval using improved Bayesian algorithm

机译:基于改进贝叶斯算法的网络多媒体信息检索

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摘要

The main thrust of this paper is application of a novel data mining approach on the log of user's feedback to improve web multimedia information retrieval performance. A user space model was constructed based on data mining, and then integrated into the original information space model to improve the accuracy of the new information space model. It can remove clutter and irrelevant text information and help to eliminate mismatch between the page author s expression and the user' s understanding and expectation. User space model was also utilized to discover the relationship between high-level and low-level features for assigning weight. The authors proposed improved Bayesian algorithm for data mining. Experiment proved that the authors' proposed algorithm was efficient.
机译:本文的主要目的是在用户反馈日志中应用一种新颖的数据挖掘方法,以提高网络多媒体信息的检索性能。基于数据挖掘构建用户空间模型,然后将其集成到原始信息空间模型中,以提高新信息空间模型的准确性。它可以消除混乱和不相关的文本信息,并有助于消除页面作者的表达与用户的理解和期望之间的不匹配。用户空间模型还被用来发现高级和低级特征之间的关系以分配权重。作者提出了一种改进的贝叶斯算法进行数据挖掘。实验证明,本文提出的算法是有效的。

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