Abstract
Technological similarity enables wine operators to share best practices, benchmark against industry standards, and identify new areas of innovation. Despite this, measuring similarity is notoriously challenging. In this paper, I use sentence embeddings on wine patent data to show how similarity compares across different models. I validate the results both internally and externally, showing large discrepancies in annual trends. The results underscore the importance of selecting suitable models for market assessment, providing a valuable primer for both wine operators and technologists.
| Original language | English |
|---|---|
| Pages (from-to) | 1-28 |
| Journal | Journal of Wine Economics |
| Volume | First View |
| Early online date | 3 Feb 2026 |
| DOIs | |
| Publication status | E-pub ahead of print - 3 Feb 2026 |
Keywords
- RAG
- Sentence embeddings
- Technological similarity
- Wine patents
- Natural Language Processing
- C81
- O31
- O33
- O34
- O38