Joint sentiment/topic modeling on text data using a boosted restricted Boltzmann Machine
暂无分享,去创建一个
[1] Jing Yu,et al. Topic correlation model for cross-modal multimedia information retrieval , 2016, Pattern Analysis and Applications.
[2] Zhiwei Ni,et al. Emerging opinion leaders in crowd unfollow crisis: a case study of mobile brands in Twitter , 2016, Pattern Analysis and Applications.
[3] Hugo Larochelle,et al. Topic Modeling of Multimodal Data: An Autoregressive Approach , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[4] Petko Bogdanov,et al. Introduction—Topic models: What they are and why they matter , 2013 .
[5] Hugo Larochelle,et al. A Neural Autoregressive Topic Model , 2012, NIPS.
[6] Stefan M. Rüger,et al. Weakly Supervised Joint Sentiment-Topic Detection from Text , 2012, IEEE Transactions on Knowledge and Data Engineering.
[7] Hugo Larochelle,et al. The Neural Autoregressive Distribution Estimator , 2011, AISTATS.
[8] Alice H. Oh,et al. Aspect and sentiment unification model for online review analysis , 2011, WSDM '11.
[9] David B. Dunson,et al. Probabilistic topic models , 2011, KDD '11 Tutorials.
[10] Tejashri Inadarchand Jain,et al. Recognizing Contextual Polarity in Phrase-Level Sentiment Analysis , 2010 .
[11] Geoffrey E. Hinton,et al. Replicated Softmax: an Undirected Topic Model , 2009, NIPS.
[12] Lillian Lee,et al. Opinion Mining and Sentiment Analysis , 2008, Found. Trends Inf. Retr..
[13] Geoffrey E. Hinton,et al. Restricted Boltzmann machines for collaborative filtering , 2007, ICML '07.
[14] John Blitzer,et al. Biographies, Bollywood, Boom-boxes and Blenders: Domain Adaptation for Sentiment Classification , 2007, ACL.
[15] Thomas L. Griffiths,et al. Probabilistic Topic Models , 2007 .
[16] Geoffrey E. Hinton,et al. Modeling Human Motion Using Binary Latent Variables , 2006, NIPS.
[17] Yiming Yang,et al. RCV1: A New Benchmark Collection for Text Categorization Research , 2004, J. Mach. Learn. Res..
[18] Bo Pang,et al. A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts , 2004, ACL.
[19] Michael I. Jordan,et al. Modeling annotated data , 2003, SIGIR.
[20] Geoffrey E. Hinton. Training Products of Experts by Minimizing Contrastive Divergence , 2002, Neural Computation.
[21] Bo Pang,et al. Thumbs up? Sentiment Classification using Machine Learning Techniques , 2002, EMNLP.
[22] Michael I. Jordan,et al. Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..
[23] Samy Bengio,et al. Modeling High-Dimensional Discrete Data with Multi-Layer Neural Networks , 1999, NIPS.
[24] Thomas Hofmann,et al. Probabilistic Latent Semantic Indexing , 1999, SIGIR Forum.
[25] Brendan J. Frey,et al. Does the Wake-sleep Algorithm Produce Good Density Estimators? , 1995, NIPS.
[26] Ken Lang,et al. NewsWeeder: Learning to Filter Netnews , 1995, ICML.
[27] David Haussler,et al. Unsupervised learning of distributions on binary vectors using two layer networks , 1991, NIPS 1991.
[28] Richard A. Harshman,et al. Indexing by Latent Semantic Analysis , 1990, J. Am. Soc. Inf. Sci..
[29] James L. McClelland,et al. James L. McClelland, David Rumelhart and the PDP Research Group, Parallel distributed processing: explorations in the microstructure of cognition . Vol. 1. Foundations . Vol. 2. Psychological and biological models . Cambridge MA: M.I.T. Press, 1987. , 1989, Journal of Child Language.
[30] James L. McClelland,et al. Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations , 1986 .
[31] Michael McGill,et al. Introduction to Modern Information Retrieval , 1983 .
[32] Geoffrey E. Hinton. A Practical Guide to Training Restricted Boltzmann Machines , 2012, Neural Networks: Tricks of the Trade.
[33] B. Schölkopf,et al. Modeling Human Motion Using Binary Latent Variables , 2007 .
[34] Miguel Á. Carreira-Perpiñán,et al. On Contrastive Divergence Learning , 2005, AISTATS.
[35] Marek R. Ogiela,et al. Multimedia tools and applications , 2005, Multimedia Tools and Applications.