ISCAS OpenIR  > 基础软件国家工程研究中心
基于Labeled-LDA模型的文本分类新算法
Alternative TitleText Classification Based on Labeled-LDA Model
李文波; 孙乐; 张大鲲
2008
Source计算机学报
Volume31Issue:4Pages:620-627
Indexed TypeEI
AbstractLDA(Latent Dirichlet Allocation)模型是近年来提出的一种能够提取文本隐含主题的非监督学习模型.通过在传统LDA模型中融入文本类别信息,文中提出了一种附加类别标签的LDA模型(Labeled-LDA).基于该模型可以在各类别上协同计算隐含主题的分配量,从而克服了传统LDA模型用于分类时强制分配隐含主题的缺陷.与传统LDA模型的实验对比表明:基于Labeled-LDA模型的文本分类新算法可以有效改进文本分类的性能,在复旦大学中文语料库上micro_F1提高约5.7%,在英文语料库20newsgroup的comp子集上micro—F-提高约3%.
Keyword文本分类
Language中文
Content Type期刊论文
URIhttp://ir.iscas.ac.cn/handle/311060/620
Collection基础软件国家工程研究中心
Recommended Citation
GB/T 7714
李文波,孙乐,张大鲲. 基于Labeled-LDA模型的文本分类新算法[J]. 计算机学报,2008,31(4):620-627.
APA 李文波,孙乐,&张大鲲.(2008).基于Labeled-LDA模型的文本分类新算法.计算机学报,31(4),620-627.
MLA 李文波,et al."基于Labeled-LDA模型的文本分类新算法".计算机学报 31.4(2008):620-627.
Files in This Item:
File Name/Size DocType Version Access License
李文波per-03.pdf(671KB) 开放获取LicenseApplication Full Text
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[李文波]'s Articles
[孙乐]'s Articles
[张大鲲]'s Articles
Baidu academic
Similar articles in Baidu academic
[李文波]'s Articles
[孙乐]'s Articles
[张大鲲]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[李文波]'s Articles
[孙乐]'s Articles
[张大鲲]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.