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…