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Received:January 16, 2015 Revised:March 12, 2015
Received:January 16, 2015 Revised:March 12, 2015
中文摘要: 利用文本分类技术对设备进行分类目前遇到的最大困难是,信息处理量的急剧增加造成分类过程中设备特征项维数的大幅增加,使得对设备的分类变得愈加困难,且效率愈来愈低.而关键词提取是提高文本分类效率的常用方法.根据设备文本描述的特点,以预先假定的初始关键词及其特征项词频来构建向量空间模型(VSM),在此基础上利用K-means算法将文本中的关键词提取出来.实验表明,基于K-means的关键词提取不仅大幅度地提高了设备分类效率,且分类准确性也得到了提高.
Abstract:Expository is the most common form in text classification. With the continuous increase of information, how to improve the efficiency of expository text classification is a hotspot in researching. Keyword extraction is used to improve the efficiency in text classification. This paper suggests to extraction keywords in the text based on the use of K-means algorithm by constructing the Vector Space Model (VSM) subject to pre-assumed initial keyword frequency. The KNN text classification algorithm verifies keywords extracting based on the use of K-means algorithm not only makes the classification accuracy slightly increased, but also reduce the dimension, thus realizing the text classification efficiency.
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基金项目:浙江省社会科学界联合会研究课题成果(2014Z052);浙江省教育厅科研项目(Y201432308)
| Author Name | Affiliation |
| CHEN Li | Laboratory and Equipment Department, Zhejiang Gongshang University, Hangzhou 310018, China College of Computer Science, Zhejiang University, Hangzhou 310058, China |
| Author Name | Affiliation |
| CHEN Li | Laboratory and Equipment Department, Zhejiang Gongshang University, Hangzhou 310018, China College of Computer Science, Zhejiang University, Hangzhou 310058, China |
引用文本：
陈立.关键词提取的K-means方法在设备分类中的运用.计算机系统应用,2015,24(12):277-282
CHEN Li.Keyword Extraction Method Based on K-means in the Application of Equipment Classification.COMPUTER SYSTEMS APPLICATIONS,2015,24(12):277-282
陈立.关键词提取的K-means方法在设备分类中的运用.计算机系统应用,2015,24(12):277-282
CHEN Li.Keyword Extraction Method Based on K-means in the Application of Equipment Classification.COMPUTER SYSTEMS APPLICATIONS,2015,24(12):277-282
