%0 Journal Article
%T 一种长文本辅助短文本的文本理解方法<br>A document understanding method for short texts by auxiliary long documents
%A 闫盈盈
%A 黄瑞章
%A 王瑞
%A 马灿
%A 刘博伟
%A 黄庭&lt
%A br&gt
%A YAN Yingying
%A HUANG Ruizhang
%A WANG Rui
%A MA Can
%A LIU Bowei
%A HUANG Ting
%J 山东大学学报（工学版）
%D 2018
%R 10.6040/j.issn.1672-3961.0.2017.402
%X 摘要： 在狄利克雷多项回归(dirichlet-multinomial regression, DMR)模型的基础上,提出一个长文本辅助短文本理解的二元狄利克雷多项回归(dual dirichlet-multinomial regression, DDMR)模型。来自不同数据源的长短文本共享一个主题集合,并采用不同的狄利克雷先验产生长短文本的主题分配,使得长文本的主题知识能够迁移到短文本中,改善短文本的理解。试验表明,DDMR模型在短文本的主题发现效果上具有较大的提升作用。<br>Abstract: Based on the dirichlet-multinomial regression(DMR)model, a dual dirichlet-multinomial regression(DDMR)model that short texts were understood by auxiliary long documents was proposed. A topic set was shared by long documents and short texts which came from different data sources, and two dirichlet priors were used to generate the topic allocation of long documents and short texts, which enabled the topic knowledge of long documents to be transferred to short texts and improved understanding of the short text. The experiments showed that the DDMR model had a great effect on the topical discovery of short texts
%K 短文本理解
%K 主题模型
%K 二元狄利克雷多项回归模型
%K &lt
%K br&gt
%K short text understanding
%K dual dirichlet-multinomial regression model
%K topic model
%U http://gxbwk.njournal.sdu.edu.cn/CN/10.6040/j.issn.1672-3961.0.2017.402