Ashley Woods

Title: Ashley Woods and Machine-Learning-Based Network Inventory Discovery.

Introduction

Ashley Woods is an inventor based in Swindon, Great Britain, and works at Ciena Corporation. Her patent work addresses the automated discovery of network inventory from raw configuration files using machine learning.

Latest Patents

Woods is associated with 1 patent, titled “Automated Discovery of Network Inventory from Raw Configuration Files Using Machine Learning.” The invention describes a network inventory discovery engine that receives unstructured configuration data about a network element and uses a trained machine-learning model to identify named entities and map their attributes to a common information model.

The model may use named entity recognition (NER), a large language model (LLM), or both. In one approach, an NER model first processes the configuration text before the resulting data is passed to an LLM. The machine-learning model can perform the role of a custom parser script, reducing reliance on scripts tailored to particular configuration formats or data sources.

Career Highlights

Woods’s patent reflects work at the intersection of machine learning and telecommunications network management. By structuring information extracted from raw configuration files, the described method aims to support automated network inventory discovery.

Collaborations

Woods’s listed coworker is Christopher Barber. The provided information does not specify their roles or the nature of their collaboration.

Conclusion

Ashley Woods’s patent describes a machine-learning approach to extracting and organizing network inventory data, connecting her work at Ciena Corporation with the automation of telecommunications network management.