Microblog Sudden Topic Detection Method Based on Regression Models and Spectral Clustering
Peng Mi · Jisuanji gongcheng · 2015
The short text of the social network-microblog has the characters of great data dimensions,fast propagation,modal diversity,low quality,etc.,which result in facing with great challenges such as high complexity,features sparse and noise interference when dealing with the data by the existing traditional topic detection and tracking method.For emerging topic detection,this paper presents a method of microblog emerging topic detection based on regression models and spectral clustering.The method quantifies the emerging frequency of microblog keywords by their trends and regression models.The unexpected words are extracted by analyzing the frequency of words changing in trends.An emerging word clustering method is designed based on spectral clustering to improve the accuracy.Experimental results based on microblog data set show that compared with baseline method,the proposed method achieves better accuracy,higher recall rate and F value.