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A Semantic Space Creation Method with an Adaptive Axis Adjustment Mechanism for Media Data Retrieval

机译:具有自适应轴调整机制的语义空间创建方法,用于媒体数据检索

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This paper presents a new semantic space creation method with an adaptive axis adjustment mechanism for media data retrieval. The semantic space is essentially required to search semantically related and appropriate information resources from media databases. In the method, data in the media databases are mapped as vectorized metadata on the semantic space. The distribution of the metadata on the semantic space is the main factor affecting the accuracy of the retrieval results. In the method, an adaptive axis adjustment mechanism is used to rotate and combine the semantic correlated axes on the semantic space, and remove axes from the semantic space. We demonstrated by experiments that when the semantic space is created and adjusted based on the semantic correlated factors, the metadata are appropriately and sharply distributed on the semantic space.
机译:本文介绍了一种新的语义空间创建方法,具有自适应轴调整机制,用于媒体数据检索。从媒体数据库中搜索语义相关和适当的信息资源,基本上需要语义空间。在该方法中,媒体数据库中的数据被映射为语义空间上的矢量化元数据。语义空间上的元数据的分布是影响检索结果准确性的主要因素。在该方法中,自适应轴调节机构用于旋转并将语义相关轴上的语义相关轴联合在语义空间上,并从语义空间中移除轴。我们通过实验证明,当基于语义相关因子创建和调整语义空间时,元数据在语义空间上适当且急剧地分布。

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