Summary of A Unified Framework to Classify Business Activities Into International Standard Industrial Classification Through Large Language Models For Circular Economy, by Xiang Li et al.
A Unified Framework to Classify Business Activities into International Standard Industrial Classification through Large Language Models for Circular Economy
by Xiang Li, Lan Zhao, Junhao Ren, Yajuan Sun, Chuan Fu Tan, Zhiquan Yeo, Gaoxi Xiao
First submitted to arxiv on: 17 Sep 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); General Economics (econ.GN)
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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 proposes an innovative approach to building recommendation systems that promote circular economy practices. By creating a centralized knowledge repository, businesses can learn from past successes and make informed decisions about waste management. However, this endeavor is hindered by the lack of a standardized framework for representing economic activities across different regions. To overcome this challenge, the authors leverage Large Language Models (LLMs) to classify textual data into the International Standard Industrial Classification (ISIC), a globally recognized framework. This approach enables businesses worldwide to categorize their economic activities using the unified ISIC standard, facilitating the creation of a centralized knowledge repository. The paper achieves 95% accuracy on a test dataset with fine-tuned GPT-2 model and contributes to the global effort of fostering sustainable circular economy practices. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The researchers are trying to help businesses be more environmentally friendly by creating a system that suggests good decisions about waste management. To do this, they need to gather information from all over the world, but it’s hard because different countries use different systems to describe their economic activities. The solution is to use special computer models that can understand and categorize text from anywhere in the world using a standard framework. This will make it easier for businesses to learn from each other and make better decisions about waste management. |
Keywords
» Artificial intelligence » Classification » Gpt
