Emotional element detection and tendency judgment based on mixed model with deep features
暂无分享,去创建一个
[1] Jeffrey Dean,et al. Efficient Estimation of Word Representations in Vector Space , 2013, ICLR.
[2] Nan Hu,et al. Ratings lead you to the product, reviews help you clinch it? The mediating role of online review sentiments on product sales , 2014, Decis. Support Syst..
[3] Babis Theodoulidis,et al. Analyzing Customer Experience Feedback Using Text Mining , 2014 .
[4] Jo Mackiewicz,et al. Product Review Users' Perceptions of Review Quality: The Role of Credibility, Informativeness, and Readability , 2014, IEEE Transactions on Professional Communication.
[5] Fuji Ren,et al. Chinese new word identification: a latent discriminative model with global features , 2011 .
[6] Wang Hongwei,et al. Sentiment Classification of Chinese Online Reviews: A Comparison between Sentences and Paragraphs , 2013 .
[7] Tang Da-quan. Word’s semantic similarity computation method based on Hownet , 2010 .
[8] Wang Wei. Opinion Object Extraction Based on the Syntax Analysis and Dependence Analysis , 2011 .
[9] Zhao Tie. Extraction of Opinion Targets Based on Shallow Parsing Features , 2011 .
[10] Frank Schweitzer,et al. Emotions in Product Reviews--Empirics and Models , 2011, 2011 IEEE Third Int'l Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third Int'l Conference on Social Computing.
[11] Thorsten Joachims,et al. Text Categorization with Support Vector Machines: Learning with Many Relevant Features , 1998, ECML.
[12] Andrew McCallum,et al. Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data , 2001, ICML.