...-consuming. Previous studies have employed Bidirectional Encoder Representations from Transformers (BERT), a state-of-the-art natural language processing (NLP) deep neural network model, to automatically analyze written requirements. Yet, it remains unclear whether BERT can sufficiently capture the nuances...

..., the current research is mainly focused on sentiment classification at the attribute, sentence, or document level [ 29 – 36 ], which would inevitably lead to information loss due to the aggregation and quantification of user feedback and opinions. Natural language processing (NLP) techniques...

... to predict design metrics from the design itself and SVS survey information. We show that incorporating natural language processing (NLP) improves prediction results across design metrics, and that clear distinctions in the predictability of certain metrics exist. Our code and additional information about...

... by the Design Theory and Methodology Committee of ASME for publication in the J ournal of M echanical D esign . 29 06 2021 03 09 2021 04 09 2021 21 09 2021 design automation new product development design evaluation image processing natural language processing deep...

.../1.4030159 [40] Zeng , J. , Liu , Y. , Su , J. , Ge , Y. , Lu , Y. , Yin , Y. , and Luo , J. , 2019 , “ Iterative Dual Domain Adaptation for Neural Machine Translation ,” Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th...

... identify the usage contexts using the survey-based method or subjectively determine them. The proposed methodology, on the other hand, uses machine learning and Natural Language Processing tools to identify and cluster usage contexts from a large volume of customer reviews. Furthermore, aspect sentiment...