Self-Taught convolutional neural networks for short text clustering
Xu, Jiaming; Xu, Bo; Wang, Peng; Zheng, Suncong; Tian, Guanhua; Zhao, Jun; Xu, Bo
刊名NEURAL NETWORKS
2017-04-01
期号88页码:22-31
关键词Semantic Clustering Neural Networks Short Text Unsupervised Learning
DOI10.1016/j.neunet.2016.12.008
文献子类Article
英文摘要Short 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.
WOS研究方向Computer Science ; Neurosciences & Neurology
语种英语
WOS记录号WOS:000397959900003
内容类型期刊论文
源URL[http://ir.ia.ac.cn/handle/173211/40804]  
专题数字内容技术与服务研究中心_听觉模型与认知计算
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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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