.... The model leverages Bidirectional Encoder Representations from Transformers (BERT) for text vector representation, combined with Text Convolutional Neural Networks (TextCNN) and Bi-directional Long Short-Term Memory (BiLSTM) networks to extract both local and global semantic features. The integration...

.... Design/methodology/approach A novel data processing method based on the BERT is presented and applied to analyze the changes and characteristics of SDG-related ESG texts from companies’ disclosures over the past decade. Specifically, ESG-related sentences are extracted from 93,277 Form 10-K filings...

... spoken language understanding called ID-SF-Fusion. Design/methodology/approach ID-SF-Fusion uses Bidirectional Encoder Representation from Transformers (BERT) and Bidirectional Long Short-Term Memory (BiLSTM) to extract effective word embedding and context vectors containing the whole sentence...

... This study collects a new dataset SQuAD_extend by crawling the QA community and uses word-graph to model the collected OQs. Next, Beam search finds the best path to get the best question. To deeply represent the features of the question, pretrained model BERT is used to model sentences. Findings...

... of traditional word embedding, the proposed model uses the pretrained Bidirectional Encoder Representations from Transformers (BERT) model as input to augment the contextual feature representation. Subsequently, with the Lattice-LSTM model, the information of characters and words is effectively utilized to avoid...

...Jiho Kim; Hanjun Lee; Hongchul Lee Purpose This paper aims to find determinants that can predict the helpfulness of online customer reviews (OCRs) with a novel approach. Design/methodology/approach The approach consists of feature engineering using various text mining techniques including BERT...

.../approach In this paper, global vectors (GloVe) and Bidirectional Encoder Representations Transformers (BERT) pre-trained word embedding are used to identify relationships between words, which helps to classify emails into their relevant categories using machine learning and deep learning models. Two...