A novel multi-layer feature fusion-based BERT-CNN for sentence representation learning and classification
Khaled Hamed Alyoubi,
Fahd Saleh Alotaibi,
Akhil Kumar
et al.
Abstract:Purpose
The purpose of this paper is to describe a new approach to sentence representation learning leading to text classification using Bidirectional Encoder Representations from Transformers (BERT) embeddings. This work proposes a novel BERT-convolutional neural network (CNN)-based model for sentence representation learning and text classification. The proposed model can be used by industries that work in the area of classification of similarity scores between the texts and sentiments and opinion analysis.
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