天津科技大学学报2017，Vol.32Issue(6)：73-78,6.DOI:10.13364/j.issn.1672-6510.20160432
基于Single-Pass的在线话题检测改进算法
An Improved Algorithm Based on Single-Pass for Online Topic Detection
摘要
Abstract
At present,the main research method of existing topic detection is to use Single-Pass and its improved algorithm for clustering analysis.However,these algorithms use a single similarity calculation method without considering the struc-tural characteristics of the text,which affects the clustering accuracy.This research hasimproved the similarity calculation method of Single-Pass and proposed a multi-similarity computation combination strategy which toke the title,abstract,time, place names and source into consideration,and used the analytic hierarchy process to calculate and assign them different weights.As food safety is a widely concerned topic,we analyzed the data about food safety in the last three years which we could get with the web crawler.The results show that the improved Single-Pass clustering algorithm proposed in this paper has a higher topic detection accuracy.关键词
网络舆情/Single-Pass/相似度计算/食品安全Key words
internet public opinion/Single-Pass/similarity calculation/food safety分类
信息技术与安全科学引用本文复制引用
马永军,刘洋,李亚军,汪睿..基于Single-Pass的在线话题检测改进算法[J].天津科技大学学报,2017,32(6):73-78,6.基金项目
天津市教委重大项目(2014ZD22) （2014ZD22）
天津市应用基础与前沿技术研究计划(14JCQNJC00300) （14JCQNJC00300）
