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fish-kong/texture-classification-based-on-BPNN-and-dictionary

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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…

☆19Aug 26, 2019Updated 6 years ago

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