计算机科学 ›› 2017, Vol. 44 ›› Issue (12): 227-231.doi: 10.11896/j.issn.1002-137X.2017.12.041
蒋宗礼,王一大
JIANG Zong-li and WANG Yi-da
摘要： 基于深度学习的特征抽取是目前数据降维问题的研究热点,堆叠自编码器作为一种较为常用的模型,无法对混有噪声及较稀疏的数据进行良好的特征表达。面向微博情感分析,通过在堆叠降噪自编码器的各隐藏层中加入稀疏因子,来解决样本数据所含噪声和稀疏性对特征抽取的影响。使用COAE评测数据集进行的情感分析实验表明所提模型分类的准确率和召回率都有所提高。
| [1] BENGIO Y,DELALLEAU O.On the expressive power of deep architectures[C]∥International Conference on Discovery Science.Springer-Verlag,2011:1. [2] KRIZHEVSKY A,SUTSKEVER I,HINTON G E.ImageNetclassification with deep convolutional neural networks[C]∥International Conference on Neural Information Processing Systems.Curran Associates Inc,2012:1097-1105. [3] DAHL G E,YU D,DENG L,et al.Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech Recognition[J].IEEE Transactions on Audio Speech & Language Processing,2012,0(1):30-42. [4] KARPATHY A,TODERICI G,SHETTY S,et al.Large-Scale Video Classification with Convolutional Neural Networks[C]∥IEEE Conference on Computer Vision and Pattern Recognition.IEEE,2014:1725-1732. [5] HINTON G E,OSINDERO S,TEH Y W.A fast learning algorithm for deep belief nets[J].Neural Computation,2006,8(7):1527-1554. [6] VINCENT P,LAROCHELLE H,BENGIO Y,et al.Extracting and composing robust features with denoising autoencoders[C]∥International Conference on Machine Learning.DBLP,2008:1096-1103. [7] CAO L L,HUANG W B,SUN F C.Building feature space of extreme learning machine with sparse denoising stacked-autoencoder[J].Neurocomputing,2016,4(PA):60-71. [8] RETRIEVAL F T I I.Opinion Mining and Sentiment Analysis[J].Foundations & Trends in Information Retrieval,2008,2(1):459-526. [9] PANG B,LEE L,VAITHYANATHAN S.Thumbs up?:sentiment classification using machine learning techniques[C]∥Conference on Empirical Methods in Natural Language Processing(Acl-02).Association for Computational Linguistics,2002:79-86. [10] STOJANOVSKI D,STREZOSKI G,MADJAROV G,et al.Twitter Sentiment Analysis Using Deep Convolutional Neural Network[C]∥Hais.2015:726-737. [11] LIU F L,YANG L,ZHANG S W,et al.Convolutional Neural Networks for Chinese Micro-blog Sentiment Analysis [J].Journal of Chinese Information Processing,2015,9(6):159-165.(in Chinese) 刘龙飞,杨亮,张绍武,等.基于卷积神经网络的微博情感倾向性分析[J].中文信息学报,2015,9(6):159-165. [12] GLOROT X,BORDES A,BENGIO Y.Domain adaptation for large-scale sentiment classification:A deep learning approach[C]∥ International Conference on Machine Learning.Omnipress,2011:513-520. [13] LIANG J,CHAI Y M,YUAN H B,et al.Deep Learning for Chinese Micro-blog Sentiment Analysis[J].Journal of Chinese Information Processing,2014,8(5):155-161.(in Chinese) 梁军,柴玉梅,原慧斌,等.基于深度学习的微博情感分析[J].中文信息学报,2014,8(5):155-161. |
| No related articles found! |
|
||
首页