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Self-Taught convolutional neural networks for short text clustering
Xu, Jiaming1; Xu, Bo1; Wang, Peng1; Zheng, Suncong1; Tian, Guanhua1; Zhao, Jun1,2; Xu, Bo1,3
Source PublicationNEURAL NETWORKS
AbstractShort text clustering is a challenging problem due to its sparseness of text representation. Herewepropose a flexible Self-Taught Convolutional neural network framework for Short Text Clustering (dubbed STC2), which can flexibly and successfully incorporate more useful semantic features and learn non-biased deep text representation in an unsupervised manner. In our framework, the original raw text features are firstly embedded into compact binary codes by using one existing unsupervised dimensionality reduction method. Then, word embeddings are explored and fed into convolutional neural networks to learn deep feature representations, meanwhile the output units are used to fit the pre-trained binary codes in the training process. Finally, we get the optimal clusters by employing K-means to cluster the learned representations. Extensive experimental results demonstrate that the proposed framework is effective, flexible and outperform several popular clustering methods when tested on three public short text datasets. (C) 2017 Elsevier Ltd. All rights reserved.
KeywordSemantic Clustering Neural Networks Short Text Unsupervised Learning
WOS HeadingsScience & Technology ; Technology ; Life Sciences & Biomedicine
Indexed BySCI
Funding OrganizationNational Natural Science Foundation of China(61602479 ; Strategic Priority Research Program of the Chinese Academy of Sciences(XDB02070005) ; 61303172 ; 61403385
WOS Research AreaComputer Science ; Neurosciences & Neurology
WOS SubjectComputer Science, Artificial Intelligence ; Neurosciences
WOS IDWOS:000397959900003
Citation statistics
Cited Times:28[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Affiliation1.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China
2.NLPR, Beijing, Peoples R China
3.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Beijing, Peoples R China
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Xu, Jiaming,Xu, Bo,Wang, Peng,et al. Self-Taught convolutional neural networks for short text clustering[J]. NEURAL NETWORKS,2017(88):22-31.
APA Xu, Jiaming.,Xu, Bo.,Wang, Peng.,Zheng, Suncong.,Tian, Guanhua.,...&Xu, Bo.(2017).Self-Taught convolutional neural networks for short text clustering.NEURAL NETWORKS(88),22-31.
MLA Xu, Jiaming,et al."Self-Taught convolutional neural networks for short text clustering".NEURAL NETWORKS .88(2017):22-31.
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