华东理工大学学报：自然科学版2011，Vol.37Issue(6)：770-774,5.
基于内容的短信分类技术
SMS Classification Technology Based on Content
陈功平 1沈明玉 2王红 1张燕平3
作者信息
- 1. 合肥工业大学计算机与信息学院,合肥230009
- 2. 六安职业技术学院信息工程系,安徽六安237158
- 3. 安徽大学计算机科学与技术学院,合月巴230039
- 折叠
摘要
Abstract
This paper researches the SMS classification technology based on the improved Bayesian method. For Chinese SMS, the document frequency （DF） was adopted for feature selection, and the selfbuilt corpus was utilized to test the classifier. The results show that the improved classifier can increase the normal pass rate of SMS. Moreover, by using new training dataset, the personalized classifier can be obtained to adapt the changes of short message and meet the user＇s requirement. The proposed classifier can finish the filtering of message by combining black and white list filtering mechanism such that the error rate of normal SMS can be reduced.关键词
短信分类/贝叶斯算法/特征提取/向量空间模型Key words
SMS classification Bayesian method feature selection vector space model分类
信息技术与安全科学引用本文复制引用
陈功平,沈明玉,王红,张燕平..基于内容的短信分类技术[J].华东理工大学学报：自然科学版,2011,37(6):770-774,5.
