本文引入最近相邻算法(Nearest Neighbor Algorithm, NNA)和字符（Text type）匹配混合方法，以决定实例的匹配程度，见图4 所示。
基于4个网页-相关网页
本文引入最近相邻算法 Nearest Neighbor Algorithm ; NNA
第二步，识别阶段，采用了一种亲笔最近相邻算法（HNN）。首先自学习预处理得到的数据，并得到对象的总的特征。再通过HNN算法来识别对象。
The second step (recognition) is achieved by using a holographic nearest-neighbor algorithm (HNN), in which vectors obtained in the preprocessing step are used as inputs to it .
新算法通过定义反映梯度变化的真假函数，能够充分考虑到未知数据网格点各象限最近相邻点的取值情况。
By this algorithm, the true and false membership functions reflecting the change of gradient are redefined. The known point is reflected with those functions.
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