Publisher
Springer Science and Business Media LLC
Subject
Cognitive Neuroscience,Computer Science Applications,Computer Vision and Pattern Recognition
Reference37 articles.
1. Bansal M, Gimpel K, Livescu K. Tailoring continuous word representations for dependency parsing. In: ACL (2). 2014. p. 809–815.
2. Bengio Y, Schwenk H, Senécal J S, Morin F, Gauvain JL. A neural probabilistic language model. J Mach Learn Res 2003;3(6):1137–1155.
3. Cambria E, Das D, Bandyopadhyay S, Feraco A. A practical guide to sentiment analysis. Switzerland: Springer, Cham; 2017.
4. Cambria E, Poria S, Bajpai R, Björn S. SenticNet 4: A Semantic resource for sentiment analysis based on conceptual primitives. In: COLING; 2016. p. 2666–2677.
5. Chaturvedi I, Ragusa E, Gastaldo P, Zunino R, Cambria E. 2017. Bayesian network based extreme learning machine for subjectivity detection. J Franklin Inst. doi: 1016/j.jfranklin.2017.06.007
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