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A Multi-kernel Convolutional Neural Network with Lstm for Sentimental Analysis
There has been tremendous victory and improvement in deep learning with the use of neural networks. Areas of image and video have benefited from this advancement, but there is room for further development in the field of sentimental analysis. Specifically, there is an abundance of text reviews of movies that require insightful classification of sentiment. This thesis first reviews machine learning literature to understand the current performance on a movie review dataset acquired from IMDb.com. Second, a combined-kernel convolutional-based Long Short-Term Memory network is proposed to perform deep learning on the challenging data. the paper also analyzes multiple approaches and variations of the model. the proposed network can achieve the highest known accuracy on the IMDb review sentiment dataset at 89.5%. the network’s success can be extended to further other fields.
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