Abstract
Text classification is an essential component in a variety of applications of natural language processing. While the deep learning-based approach is becoming more popular, using vectors of word as an input for the models has proved to be a good way for the machine to learn the relation between words in a document. This paper proposes a solution for the text classification using hybrid deep learning approaches. Every existing deep learning approach has its own advantages and the hybrid deep learning model we are introducing is the combination of the superior features of CNN and LSTM models. The proposed models CNN-LSTM, LSTM-CNN show enhanced accuracy over another approach.
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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Hung, B.T. (2019). Document Classification by Using Hybrid Deep Learning Approach. In: Vinh, P., Rakib, A. (eds) Context-Aware Systems and Applications, and Nature of Computation and Communication. ICCASA ICTCC 2019 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 298. Springer, Cham. https://doi.org/10.1007/978-3-030-34365-1_13
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DOI: https://doi.org/10.1007/978-3-030-34365-1_13
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