%Aigaion2 BibTeX export from HES SO Valais Publications
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@INPROCEEDINGS{,
     author = {Liu, Zhan and Bertaud, Adrien and Darbellay, Anne and Glassey Balet, Nicole},
   keywords = {Cross-lingual translation, Decision support systems, Human-in-the-loop AI, Hybrid AI models, Intelligent systems, Media prediction, Multilingual newsrooms},
      month = mar,
      title = {Intelligent Decision Support for Article Translation in Multilingual Newsrooms},
  booktitle = {41th ACM/SIGAPP Symposium on Applied Computing},
       year = {2026},
      pages = {806-814},
  publisher = {ACM},
   location = {Thessaloniki, Greece},
        doi = {https://doi.org/10.1145/3748522.3779719},
   abstract = {We present an intelligent decision support system, powered by AI-driven prediction, designed to assist multilingual newsrooms in selecting articles for cross-regional translation as part of the digital transformation of journalism. Trained on 15,933 German-language articles from a major Swiss publisher, the system combines multilingual BERT embeddings with 41 engineered features and incorporates real-time editorial feedback through an active learning loop. It achieves an accuracy of 85.0\%. During deployment, F1 improved from 77.5\% to 81.2\% after four weeks of feedback-driven exemplar refresh. Ablation studies indicate that sentiment polarity, regional relevance, and person-type named entities are the most influential features. The interface highlights key factors, ensuring transparency and consistency with editorial practice. By pairing hybrid NLP with human-in-the-loop prompting, the approach operationalizes intelligent translation triage in a live newsroom while preserving human control over final decisions.}
}