针对复杂对象的图像检索，提出一种基于逻辑运算的概率模型。
A logical operation-based probability model for image retrieval was presented.
首先叙述了基于内容的图像检索的系统模型和特点，接着针对颜色、纹理和形状进行了概率特征提取、相似度量等的进一步具体分析讨论。
It presents the model and feature of content-based image retrieval system, and then discusses some methods of feature abstraction and similarity measurement based on color, texture and shape.
本文在向量空间模型和概率推理网络的基础上提出了一个基于关键词与概念相结合的混合信息检索模型。
We bring forward a hybrid model that is based on a combination of keywords and concept. The hybrid model is built on vector space model and probabilistic reasoning network.
实验结果表明：在概率潜在语义检索模型中，词的正确切分能提高检索的平均精度。
Experimental results indicate that accurate segmentation can improve the effectiveness of retrieval based on PLSA.
目前已有的检索模型有布尔模型、向量模型、概率模型以及以上三个经典模型的变形模型。
At present there are the Boolean model, the vector space model, the probabilistic model and distorted model of the above three classic models.
目前已有的检索模型有布尔模型、向量模型、概率模型以及以上三个经典模型的变形模型。
At present there are the Boolean model, the vector space model, the probabilistic model and distorted model of the above three classic models.
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