本文提出了一种语义聚类和扩展的新方法，称为有指导的统计隐含语义标引(SPLSI)算法。
This paper proposes a new method for meaning clustering called 'Supervised Probabilistic Latent Semantic Indexing' (SPLSI).
同时提出一种基于内容的图像标引与检索系统结构，能自适应的在图像语义库中添加较为成功的语义表述。
The same time, it raise a new structure of system of content based image indexing and retrieval which can adapt oneself for adding successful semantic users did to semantic database.
传统的采用主题词和关键词对文档进行标引的方法，由于不能提供语义推理而越来越不适合目前的网络环境。
The traditional way of document indexing based on subject words and can't work well in the network environment because of the lack of the ability of semantic deducing.
本文通过对现有基于内容图像标引及检索技术的简要介绍，提出应在现有系统中增加图像的高层语义概念描述，以更接近于人的视觉效果。
This paper introduced the technology of content based image indexing and retrieval concisely. It propose to increase high level semantic describe of image to approach visual sense of human being.
本文通过对现有基于内容图像标引及检索技术的简要介绍，提出应在现有系统中增加图像的高层语义概念描述，以更接近于人的视觉效果。
This paper introduced the technology of content based image indexing and retrieval concisely. It propose to increase high level semantic describe of image to approach visual sense of human being.
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