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BowTie - a deep learning feedforward neural network for sentiment analysis



Apostol T. Vassilev


How to model and encode the semantics of human-written text and select the type of neural network to process it are not settled issues in sentiment analysis. Accuracy and transferability are critical issues in machine learning in general. These properties are closely related to the loss estimates for the trained model. I present a computationally- efficient and accurate feedforward neural network for sentiment prediction capable of maintaining low losses. When coupled with an effective semantics model of the text, it provides highly accurate models with low losses. Experimental results on representative benchmark datasets and comparisons to other methods.
Proceedings Title
The 5th International Conference on machine Learning, Optimization and Data science - LOD 2019
Conference Dates
September 10-13, 2019
Conference Location
Siena, -1
Conference Title
LOD 2019


Deep learning, Sentiment analysis, Natural Language Processing
Created January 3, 2020, Updated April 4, 2020