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Advances, Systems and Applications

Journal of Cloud Computing Cover Image

Table 5 Comparison among our proposed model and previous works

From: ConvLSTMConv network: a deep learning approach for sentiment analysis in cloud computing

AuthorAccuracy%Method Description
Pang and Lee[27]87.20%Subjective summarization based on minimum cuts
Kennedy and Inkpen [28]86.20%Contextual Valence Shifters
Martineau and Finin [29]88.10%TFIDF Weighting
Maas et al. [30]88.90%A mix of unsupervised and supervised techniques to learn word vectors
Tu et al.[31]88.50%Word embedding using vector kernel + tree-based word dependency integrated with grammar relations
Nguyen et al.[32]87.95%Two-step classification of support vector machine and Naive Bayes
Our proposed model89.02%The combination of the convolution layer and the LSTM layer and the convolution layer (ConvLSTMConv)