[ICWR 2025] Transformer-Based Named Entity Recognition for Automated Server Provisioning

Hossein Damavandi, Hasan Jalali, & Boshra Pishgoo

🚀 Official implementation for Transformer-Based Named Entity Recognition for Automated Server Provisioning.

This repository demonstrates a framework that bridges voice commands to server configurations using advanced transformer models. The approach extracts and processes key entities required for provisioning automated, scalable, and intelligent infrastructure solutions.

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📄 For more details, refer to the paper on IEEE Xplore.
🔓 The full-text is also available on ResearchGate.

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Try the Demo

Extract entities from voice and text using the app: [HERE].

The Architecture

Dataset

The dataset used for training and evaluation is located in the dataset directory.

Train

The training code is available in training.ipynb.

Inference

The inference code is available in inference.ipynb.

Citation

If you use this work in your research, please cite:

@inproceedings{damavandi2025transformer,
  title={Transformer-Based Named Entity Recognition for Automated Server Provisioning},
  author={Damavandi, Hossein and Jalali, Hasan and Pishgoo, Boshra},
  booktitle={2025 11th International Conference on Web Research (ICWR)},
  pages={534--540},
  year={2025},
  organization={IEEE}
}

Contact

For any inquiries or contributions, please contact hossein.damavandi@email.kntu.ac.ir or hasanjalali@ut.ac.ir.