CASIA OpenIR  > 数字内容技术与服务研究中心  > 听觉模型与认知计算
Learning Document Semantic Representation with Hybrid Deep Belief Network
Yan, Yan1; Yin, Xu-Cheng1; Li, Sujian2; Yang, Mingyuan1; Hao, Hong-Wei3
Source PublicationCOMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE
2015
SubtypeArticle
AbstractHigh-level abstraction, for example, semantic representation, is vital for document classification and retrieval. However, how to learn document semantic representation is still a topic open for discussion in information retrieval and natural language processing. In this paper, we propose a new Hybrid Deep Belief Network (HDBN) which uses Deep Boltzmann Machine (DBM) on the lower layers together with Deep Belief Network (DBN) on the upper layers. The advantage of DBM is that it employs undirected connection when training weight parameters which can be used to sample the states of nodes on each layer more successfully and it is also an effective way to remove noise from the different document representation type; the DBN can enhance extract abstract of the document in depth, making the model learn sufficient semantic representation. At the same time, we explore different input strategies for semantic distributed representation. Experimental results show that our model using the word embedding instead of single word has better performance.
WOS HeadingsScience & Technology ; Life Sciences & Biomedicine
Indexed BySCI
Language英语
WOS Research AreaMathematical & Computational Biology ; Neurosciences & Neurology
WOS SubjectMathematical & Computational Biology ; Neurosciences
WOS IDWOS:000352360600001
Citation statistics
Cited Times:5[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/8127
Collection数字内容技术与服务研究中心_听觉模型与认知计算
Affiliation1.Univ Sci & Technol Beijing, Sch Comp & Commun Engn, Dept Comp Sci & Technol, Beijing 100083, Peoples R China
2.Peking Univ, Minist Educ, Key Lab Computat Linguist, Beijing 100871, Peoples R China
3.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Yan, Yan,Yin, Xu-Cheng,Li, Sujian,et al. Learning Document Semantic Representation with Hybrid Deep Belief Network[J]. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE,2015.
APA Yan, Yan,Yin, Xu-Cheng,Li, Sujian,Yang, Mingyuan,&Hao, Hong-Wei.(2015).Learning Document Semantic Representation with Hybrid Deep Belief Network.COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE.
MLA Yan, Yan,et al."Learning Document Semantic Representation with Hybrid Deep Belief Network".COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE (2015).
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