摘要
文章针对办公信息管理中公文管理智能化程度尚不够高的这一特点,重点研究了贝叶斯文本分类技术在办公信息系统中公文分类的应用。提出了一种基于向量空间模型的贝叶斯文本分类技术并将其应用到高校公文智能办公系统的实现中,给出了详细的算法流程及设计步骤,最后给出了示例的实验结果及分析。实验结果表明,当训练集合数目有限时,该方法能够有效提高电子邮件的分类准确率,该文本分类技术的应用可以有效提高办公系统公文管理的智能性。
Aiming at the poor intelligence management of office information, this paper focuses on the research of the classification of information technology in the office systems. A Bayes text classification technique based on vector space model is put forward and is applied to colleges and universities in document handling. A detailed algorithm of the flow is given, and finally the example of the experimental results is provided. The results show that this approach can improve the accuracy of document classification especially when the size of training set is small and can effectively improve the office system＇s intelligence management.
出处
《南昌航空大学学报（自然科学版）》
CAS
2009年第4期66-70,共5页
Journal of Nanchang Hangkong University(Natural Sciences)
基金
高校青年教师自选课题基金"数据挖掘中聚类问题的若干研究"(EC200704037)
关键词
向量空间模型
公文分类
办公自动化
vector space model（VSM）
text classification
office automation
