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Title:
smoothing lda model for text categorization
Author: Li Wenbo ; Sun Le ; Feng Yuanyong ; Zhang Dakun
Source: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Conference Name: 4th Asia Information Retrieval Symposium
Conference Date: JAN 15-18,
Issued Date: 2008
Conference Place: Harbin, PEOPLES R CHINA
Keyword: text categorization ; Latent Dirichlet Allocation ; smoothing graphical model
Publisher: INFORMATION RETRIEVAL TECHNOLOGY
Publish Place: HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY
ISSN: 0302-9743
ISBN: 978-3-540-68633-0
Department: Li, Wenbo; Sun, Le; Feng, Yuanyong; Zhang, Dakun Chinese Acad Sci, Inst Software, Beijing 100190, Peoples R China.
Sponsorship: Microsoft Research Asia
English Abstract: Latent Dirichlet Allocation (LDA) is a document level language model. In general, LDA employ the symmetry Dirichlet distribution as prior of the topic-words distributions to implement model smoothing. In this paper, we propose a data-driven sm
Content Type: 会议论文
URI: http://ir.iscas.ac.cn/handle/311060/10646
Appears in Collections:基础软件国家工程研究中心_会议论文

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Recommended Citation:
Li Wenbo,Sun Le,Feng Yuanyong,et al. smoothing lda model for text categorization[C]. 见:4th Asia Information Retrieval Symposium. Harbin, PEOPLES R CHINA. JAN 15-18,.
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