In the first model they observe the co-occurrence of keywords with image regions which are created using a regular grid. And they annotate the images by the association probability.
共现模型将图像划分成规则区域，根据图像区域和关键词的共现概率来标注图像，即观察关键词与图像区域的联合发生概率。
This paper studies two representative annotation algorithms using probability models firstly. They are the Co-occurrence model and the Translation model.
本文首先研究两种具有代表性的基于概率建模的标注算法，分别是共现模型和翻译模型。
The word translation probability was calculated by 4 common co-occurrence models in bilingual corpus, and the translation equivalence was extracted according to translation probability.
基于双语语料库可自动抽取翻译等价对：利用4种常见的数学模型来计算任意两个词的共现频率，以共现频率的高低来获取翻译等价对。
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