Telecom complaint hot topic detection method based on density peaks clustering - Jun JIANG; Hua HUANG; Tiaojuan REN; Denghui ZHANG (Dianxin kexue)
In view of the lack of effective detection methods for hot topics in telecom industry,a method of complaint hotspots detection based on density peaks clustering algorithm was proposed.Firstly,a special vocabulary for telecommunication industry was established to segment the complaint samples.The vector space model was used to represent the text segmentation.Then,the similarity and density of the text segmentation were calculated,and the clustering analysis of the words was carried out by using the density peaks clustering algorithm.Finally,keywords were selected and sorted by clustering.This method was applied to the complaint hotspots detection tasks within a telecom company.The results show that this method is effective and has practical application value.