面向舆情分析的短文本频繁模式聚类算法

基于短文本的舆情分析是当前信息挖掘与情感分析领域的研究重点,针对网络环境中大量的短文本信息的鲜明特点,本文突破了传统基于词的分类方法,提出一种基于后缀数组频繁模式发现的聚类算法,利用后缀数组频繁模式精确去重算法得到关键词库,结合局部性原理对位置点聚类之后作有意义字串挖掘,进而进行文本舆情分析,以便及时动态了解网络群体的情感方向以及社会舆情热点。

Short Text Frequent Pattern Clustering Algorithm for Public Opinion Analysis

The analysis of public opinion based on short text is the focus of the field of information mining and sensation analysis.Different from the traditional classification method based on words,a clustering algorithm,which based on suffix arrays is proposed.By removeing repetitive string accurately,meaningful strings are obtained after the clustering analysis of repeat string alterations in accordance with the principle of position.Public opinion toward these meaningful strings are analyzed and the dynamic emot...