计算机与数字工程2024，Vol.52Issue(2)：496-501,6.DOI:10.3969/j.issn.1672-9722.2024.02.037
基于自适应特征词的微博噪音过滤方法
Microblog Noise Filtering Method Based on Self-adaptive Characteristics
张晓瑜 1高扬 2苗星星 1祝永霞3
作者信息
- 1. 中国人民解放军32317部队 乌鲁木齐 830000
- 2. 中国人民解放军32319部队 乌鲁木齐 830000
- 3. 陆军边海防学院 乌鲁木齐 830000
- 折叠
摘要
Abstract
Microblog noise filtering can remove garbage samples and reduce data scale.The noise seed words are generated by the clustering algorithm.FP-Growth algorithm is used to expand the seed words on unlabeled data to generate a noise feature word dictionary.Combining user and content characteristics,the support vector machine model is introduced to filter noise microblogs.The experimental results shows that the precision is 84%,the recall is 79%,the F1 value is 81%,which proves that the noise char-acteristics generated by the model can help to improve the filtering effect of microblog.关键词
微博/自适应/噪音特征词/支持向量机Key words
microblog/self-adaptive/noise characteristics/SVM分类
信息技术与安全科学引用本文复制引用
张晓瑜,高扬,苗星星,祝永霞..基于自适应特征词的微博噪音过滤方法[J].计算机与数字工程,2024,52(2):496-501,6.
