| 基于模糊向量空间的文本分类方法 |
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| 引用本文： | 郑凤萍,刘春雨.基于模糊向量空间的文本分类方法[J].情报科学,2007,25(4):588-591. |
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| 作者姓名： | 郑凤萍 刘春雨 |
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| 作者单位： | 1. 大庆石油学院,图书馆,黑龙江,大庆,163318
2. 吉林大学,管理学院,吉林,长春,130022 |
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| 摘 要： | 本文针对文本自动分类问题，提出了一种基于模糊向量空间模型和径向基函数网络的分类方法。网络由输入层、隐层和输出层组成。输入层完成分类样本的输入，隐层提取输入样本所隐含的模式特征，将分类结果在输出层表现出来。该方法在特征提取时充分考虑了特征项在文档中的位置信息，构造出模糊特征向量，使自动分类更接近手工分类方法。以中国期刊网全文数据库部分文档数据为例验证了该方法的有效性。
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| 关 键 词： | 数据挖掘 特征提取 神经网络 文本分类 |
| 文章编号： | 1007-7634（2007）04-0588-04 |
| 收稿时间： | 2006-10-31 |
| 修稿时间： | 2006-10-31 |
Document Classification Method Based on Fuzzy Vector Space |
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| ZHENG Feng-ping,LIU Chun-yu.Document Classification Method Based on Fuzzy Vector Space[J].Information Science,2007,25(4):588-591. |
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| Authors: | ZHENG Feng-ping LIU Chun-yu |
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| Institution: | 1. Library of Daqing Petroleum Institute, Daqing 163318, China; 2. Management School of Jilin University, Changchun 130022, China |
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| Abstract: | Aiming to document classification in data mining, a classification method based on fuzzy vector space model and radial basis function network is presented in this paper. The network includes input layer, hidden layer and output layer. Input layer performs import of samples, hidden layer extracts model characters of samples and output layer presents classification results. The information of its locality in the document is considered while the keywords of model characters are extracted. The classification results of this method are more precise than that of general method because fuzzy eigenvectors are applied. Finally the availability of model and algorithms is proved by classification of some documents in china periodical document database. |
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| Keywords: | data mining characters extraction neural network document classification |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
