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Author/Affiliation: Yoko KonnoOpen AccessArticle
9 Pages, 811 KB 
Japanese Abstractive Text Summarization using BERT
Abstract:
In this study, we developed and evaluated an automatic abstractive summarization algorithm in Japanese using a neural network. We used a sequence-to-sequence encoder-decoder model for practical purposes. The encoder obtained a feature-based input vector of sentences using the bidirectional encoder representations from transformers (BERT) technique. A transformer-based decoder returned the summary sentence from the output…
Read More(This article belongs to the SP9 (Special Issue on Multidisciplinary Innovation in Engineering Science & Technology 2020) & Section Interdisciplinary Applications of Computer Science (CSI))