| 基于 K-means 的政府公文聚类方法 |
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| 引用本文： | 王荻智,李建宏,施运梅.基于 K-means 的政府公文聚类方法[J].教育技术导刊,2020,19(6):201-204. |
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| 作者姓名： | 王荻智 李建宏 施运梅 |
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| 作者单位： | 北京信息科技大学 计算机学院，北京 100101 |
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| 基金项目： | 国家重点研发计划项目（2018YFB1004100）；北京信息科技大学 2019 年人才培养质量提高经费项目（5101923400） |
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| 摘 要： | 政府公文数量巨大，不同政府网站公文分类规则不一 ，在引用和参考公文时可能发生混淆 。针对该问题，基于政府公文题目、摘要和正文内容，采用 K-means 算法对公文进行分类。首先对政府公文进行分词及去停用词等数据预处理操作，再通过词频—逆文档频率（TF-IDF）权值计算方法，将处理后的政府文本信息转换成二维矩阵，然后采用 K-means 算法进行聚类。使用清华大学 THUCTC 文本分类系统对公文聚类结果进行测试。实验结果表明，采用 K-means 算法对公文进行聚类，准确率达到 82.93%，远高于政府网站公文分类准确率。
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| 关 键 词： | 文本聚类 词频—逆文档频率 K-means 算法 |
| 收稿时间： | 2019-10-11 |
Methods of Government Document Clustering Based on K-means Algorithm |
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| WANG Di-zhi,LI Jian-hong,SHI Yun-mei.Methods of Government Document Clustering Based on K-means Algorithm[J].Introduction of Educational Technology,2020,19(6):201-204. |
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| Authors: | WANG Di-zhi LI Jian-hong SHI Yun-mei |
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| Institution: | Computer School，Beijing Information Science and Technology University，Beijing 100101，China |
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| Abstract: | The number of government documents is huge，and each government body uses different methods to classify their documents，but the results are not satisfactory. The article proposes a method which uses K-means algorithm to classify the government documents based on their titles，abstracts and contents. Firstly，the government documents are preprocessed by word segmentation，removing stop words and etc. Then TF-IDF weight calculation algorithm is used to quantify the government documents. Finally，K-means is utilized to cluster the government documents. THUCTC developed by Tsinghua University is used to test the results of the document classification and the accuracy rate reaches 82.93%，the experiment shows that K-means can achieve higher clustering effects. |
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| Keywords: | document clustering TF-IDF K-means algorithm |
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