On helping users in writing network slice intents through NLP and User Profiling

Author:

Caldelli R.1,Castoldi P.2,Gharbaoui M.2,Martini B.1,Matarazzo M.1,Sciarrone F.1

Affiliation:

1. Universitas Mercatorum,Italy

2. Scuola Superiore Sant’Anna,Italy

Publisher

IEEE

Reference27 articles.

1. LossLeaP: Learning to Predict for Intent-Based Networking

2. Slicing the core network and radio access network domains through intent-based networking for 5G networks;abbas,2020

3. Natural language processing: state of the art, current trends and challenges;khurana;Multimedia Tools and Applications,2022

4. IBNSlicing: Intent-Based Network Slicing Framework for 5G Networks using Deep Learning

5. Introduction to the artificial intelligence that can be applied to the network automation journey;moisio;arXiv preprint 1911 03894,2022

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Enhancing conversational ai with the Rasa framework: intent understanding and NLU pipeline optimization;Journal of Modern Science;2024-08-20

2. Exploring Large Language Models in Intent Acquisition and Translation;2024 IEEE 10th International Conference on Network Softwarization (NetSoft);2024-06-24

3. LLM-enabled Intent-driven Service Configuration for Next Generation Networks;2024 IEEE 10th International Conference on Network Softwarization (NetSoft);2024-06-24

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