Journal of Engineering, Project, and Production Management, 2026, 16(6), 2026-298
Adaptive BERT for Semantic Alignment and Intelligent Triage of Multilingual Inquiries in Cross-Border E-Commerce
Associate Professor, School of Digital Commerce, Wuxi Vocational Institute of Commerce, Wuxi, 214153, China, E-mail: DanyanChendy@outlook.com
Project Management
Received March 4, 2026; revised April 30, 2026; July 14, 2026; accepted September 9, 2026
Available online September 20, 2026
Abstract: Currently, in the field of cross-border e-commerce, there are problems such as insufficient adaptation of general pre-training models to domain features, significant differences in the semantic gap between English-Chinese cross-language and English-Russian scenarios, low training efficiency and high deployment costs when implementing complex models. In this regard, the study proposes a domain-adaptive Multilingual Bidirectional Encoder Representations from Transformers (MBERT) model that integrates a Domain Adaptation Layer (DAL) and a Cross-Language Alignment Module (CLAM). This study first performs domain adaptation optimization through pre-training a Domain-Distinguish Task (DDT) BERT model. On this basis, MBERT is used to provide the model with a cross-language semantic representation, and the DDT mechanism and Retrieval-Augmented Generation (RAG) technology are finally integrated. The experimental results showed that, on the SemEval-2016 attribute-level emotion annotation data set, the proposed model achieved average accuracies of 82.2%, 83.2%, and 88.0% in the English-Chinese, English-Russian, and English-Spanish scenarios, respectively, demonstrating the best performance. Pre-training took 6.3 h and converged in 16 rounds. Inference took 19ms/sentence and occupied 9GB of video memory. Adding DAL alone increased the F1 value in the English-Spanish scene by 4.1%, and adding CLAM alone increased the English-Chinese accuracy by 4.2%.
Keywords: Domain adaptation; bidirectional encoder representations from transformers (BERT); multi-language; semantic alignment; cross-border e-commerce.
Copyright © Journal of Engineering, Project, and Production Management (EPPM-Journal).
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.
Requests for reprints and permissions at eppm.journal@gmail.com.
Citation: Chen, D. (2026). Adaptive BERT for Semantic Alignment and Intelligent Triage of Multilingual Inquiries in Cross-Border E-Commerce. Journal of Engineering, Project, and Production Management, 16(6), 2026-298.
