This repository contains supplementary material for my PhD thesis "Towards automatically generating supply chain maps from natural language text". This repository shall also provide pointers to the academic papers that have been written as part of this project.
The material contains the following:
- Distinction between supply chain and related concepts
- Supply chain resilience
- A critical reflection on the value of supply chain maps
- Inter- and intra-annotator agreement
- Use cases of structural supply chain visibility
The following publications resulted from the research conducted as part of the PhD.
Conference paper "Towards automatically generating supply chain maps from natural language text" (2018)
Alexandra Brintrup, Simon Baker, Philip Woodall, and Duncan McFarlane.Towards automatically generating supply chain maps from natural language text. IFAC-PapersOnLine, 51(11):1726 – 1731, 2018. ISSN 2405-8963. 16th IFAC Symposium on Information Control Problems in Manufacturing INCOM 2018.
https://www.sciencedirect.com/science/article/pii/S2405896318313284
You can also contact the author here (create an 'Issue' in this repo) to get access to the manuscript.
Pascal Wichmann, Alexandra Brintrup, Simon Baker, Philip Woodall & Duncan McFarlane (2020) Extracting supply chain maps from news articles using deep neural networks, International Journal of Production Research, 58:17, 5320-5336, DOI: 10.1080/00207543.2020.1720925
https://www.tandfonline.com/doi/abs/10.1080/00207543.2020.1720925
You can also contact the author here (create an 'Issue' in this repo) to get access to the manuscript.
Please see here for material supplementary to the IJPR paper and code examples: https://github.com/pwichmann/supply_chain_mining
Versed AI is a new Cambridge University spin-out being formed by a post-doc and post-graduates from several different university departments. The team has developed Natural Language Processing (NLP) and Machine Learning (ML) technology for business intelligence purposes.
The technology can text-mine millions of news articles, business reports and social media for relationships between organisations, companies, products, and people. This information can be used to create vast knowledge networks that artificial intelligence is applied to in order to discover patterns and infer missing or unknown knowledge. These networks have many useful applications including predicting future relations and discovering information from the network structure. The first application the team intends to focus on is to automatically extract supply chain maps.
Among other achievements, the Versed AI team has won the Entrepreneurial Postdocs of Cambridge business plan competition (including a £20k investment sponsored by Cambridge Enterprise).