Summary of Natural Language Processing in Patents: a Survey, by Lekang Jiang et al.
Natural Language Processing in Patents: A Survey
by Lekang Jiang, Stephan Goetz
First submitted to arxiv on: 6 Mar 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper introduces a comprehensive guide for natural language processing (NLP) researchers to effectively apply large language models (LLMs) in the patent domain. It provides an overview of patent characteristics, highlighting the complexity of patent processing and the potential of LLMs in this area. The authors demonstrate how NLP can be used for patent analysis and generation, showcasing a range of tasks including nine patent analysis and four patent generation tasks. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper helps researchers apply large language models to patents, which have unique characteristics. It explains what makes patents special and shows how LLMs can be used to analyze and create new patents. The authors demonstrate different ways NLP can be used in this area, including analyzing existing patents and generating new ones. |
Keywords
» Artificial intelligence » Natural language processing » Nlp
