所属单位：

信息与控制工程学院

发表刊物：

Advacned in Intelligent System Research

关键字：

中文关键字：MapReduce;k均值;隐语义模型，英文关键字：MapReduce;Kmeans;Hidden topic model

摘要：

In consideration of the features of micro-blogging content such as short text, sparse feature words and the huge scale, a method to detect micro-blogging hot topic was proposed in this paper based on MapReduce programming model. This method first employs the hidden topic analysis to solve the problem of short micro-blogging content and sparse feature words. Then the CURE algorithm is used to alleviate the problem that the Kmeans algorithm is sensitive to the initial points. Finally, the hot topic clustering results are obtained through the parallel Kmeans clustering algorithm based on the MapReduce programming model. The experimental results show that proposed method can effectively improve the micro-blogging hot topic detection efficiency.

备注：

张翔

合写作者：

吝睿涛

第一作者：

张翔,王茹,董丽丽

论文类型：

期刊论文

卷号：

卷：101

期号：

期：

页面范围：

页：104-108

是否译文：

否

发表时间：

2014-01-01