微型电脑应用

为了提升文本查重水平，提出基于分词矩阵和自然语言处理技术的文本模糊匹配查重方法。所提出的方法利用自然语言处理技术中的N-gram模型对文本进行分词处理后，利用自然语言处理技术中的one-hot模型对文本自然语言进行数字化转换，计算文本词汇权重，得到文本关键词；以文本关键词为基础，构造文本矩阵，利用分词矩阵对文本进行模糊匹配查重。实验结果表明：所提出的方法对文本分词精度较高，分词切词速度较快；可有效提取文本关键词，并有效对文本进行模糊匹配查重，具备较为显著的应用效果。

In order to improve the level of text duplicate checking technology, a text fuzzy matching duplicate checking method based on word segmentation matrix and natural language processing technology is proposed. The proposed method uses the N-gram model of natural language processing technology to segment the text, uses the one-hot model of natural language processing technology to digitally transform the text natural language, and calculates the weight of the text vocabulary to get the text keywords. Based on text keywords, a text matrix is constructed, and the word segmentation matrix is used to perform fuzzy matching duplicate checking for the text. The experimental results show that the proposed method has high accuracy in text segmentation and the segmentation speed is fast. It can effectively extract text keywords and perform fuzzy matching duplicate checking for the text, which has significant application effects.