计算机与现代化Issue(7)：91-94,4.DOI:10.3969/j.issn.1006-2475.2016.07.018
时序化 LDA 的舆情文本动态主题提取
Time Constrained LDA for Topic Extraction of Public Opinion Texts
摘要
Abstract
With the development of Internet , a large number of public opinion texts have been produced , and the hot topics and trends can be found by topics extraction from these texts .Because of the huge amount of the texts , and the dynamic changes of topics, a TC-LDA (Time Constrained LDA) model is proposed.TC-LDA can transform the text data into the topic vector and greatly reduce the dimension of public opinion texts , and implements the LDA ’ s timing conversion by adding the time constraint , which can improve the ability of LDA to capture the dynamic topic words .Experiments show that the accuracy and recall rate of TC-LDA is better than that of the similar topic model .关键词
LDA/主题模型/时间约束Key words
latent dirichlet allocation/topic model/time constraint/topic words分类
信息技术与安全科学引用本文复制引用
万红新,彭云,郑睿颖..时序化 LDA 的舆情文本动态主题提取[J].计算机与现代化,2016,(7):91-94,4.基金项目
江西省社会科学规划项目（14TQ04）；江西省高校人文社会科学研究项目 （）
