fish-kong / texture-classification-based-on-BPNN-and-dictionary
代码主要包括:1。特征提取 首先对文本信息进行分词处理,采用基于字符串匹配的方法: 假如一段叫:李二狗就是一个傻逼 基于匹配的方法就是依次截取一到多个词,并与字典库进行匹配。如二狗,如果匹配到字典中有这个词,则将其分为一个词;当取到“狗就”,发现字典中没有与之匹配的,则说明这个不是一个词语,进行顺序操作,最优将这段话分为:李 二狗 就是 一个 傻逼。 2. 得到分词后的文本之后,就是转换成数字编码,因此电脑没办法识别汉字。这一部分叫特征表示,即用数字的方式表示中文文本,采用的方法是基于词带模型的特征表示: 词带就是字典--程序中那个dictionary.mat。我们将分词处理之后的文本中的每一个词语,分别与字典中的词进行匹配,只要出现过就为1,否则为0。 如 字典中的词含有:李…
☆20Updated 5 years ago
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