所属单位：

信息与控制工程学院

发表刊物：

Machine Tool Technology,Mechatronics and Information Engineering

关键字：

中文关键字：中文微博;话题追踪;LDA;Bagging，英文关键字：Chinese micro-blogging;,topic tracking;LDA;Bagging

摘要：

To the problem of Chinese micro-blogging topic tracking, a method combined LDA model and Bagging of ensemble learning was proposed. The method firstly used the LDA hidden topic modeling, effectively solved the issue that the dataset’s sparsity of the short text, then made the C4.5 decision tree as a weak classifier, through examples resampling to obtain multiple training set, compounding the training sets according to the voting rule, and ultimately getting the similarity of the micro-blogging topic. Experiments show that, compared with the model based on single vector model, classical TF-IDF and the tracking method of C.45Bagging similarity computing, this method have a better performance on precision, recall ratio and F1 value

备注：

张翔

合写作者：

尚勃,朱雨洁

第一作者：

张翔,董丽丽

论文类型：

期刊论文

卷号：

卷：644

期号：

期：

页面范围：

页：2816-2821

是否译文：

否

发表时间：

2014-01-01