Improved Text Clustering Algorithm and Application in Microblogging Public Opinion Analysis
Improved Text Clustering Algorithm and Application in Microblogging Public Opinion Analysis
复制标题
DOI：
10.1109/wcse.2013.9
复制
发表时间：
2013-12
期刊：
影响因子：
--
通讯作者：
Yiyang Wang;Li Wang;Jing Qi;Zhong Qian;Bo Xu;Chao Lei;Yuexiang Yang;Huali Cai
中科院分区：
文献类型：
--
作者：
Yiyang Wang;Li Wang;Jing Qi;Zhong Qian;Bo Xu;Chao Lei;Yuexiang Yang;Huali Cai
在K-Means算法和凝聚层次聚类算法的基础上，对聚类算法在文本挖掘中的应用进行了改进。实验结果表明，通过文本的矢量表示、文本相似度计算和聚类算法的实现，提高了热点话题检测的准确率和效率。
Based on K-Means algorithm and agglomerative hierarchical clustering algorithm, improvement was made regarding the use of clustering algorithm in the application of text mining. It was verified that the accuracy and efficiency of hot topic detection had been enhanced via vector representation of the text, text similarity calculation, and implementation of clustering algorithm.