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Building Data-Driven Occupation Taxonomies: A Bottom-Up Multi-Stage Approach via Semantic Clustering and Multi-Agent Collaboration

Requirements

conda create --name climb python=3.10 
conda activate climb
pip install -r requirements.txt

Environment

  • rename the .env.example to .env and fill in the API keys

Usage

Data

unzip the data.zip and put it in the data folder

Palestine

run src/0.palestine.ipynb

Botswana

run src/1.botswana.ipynb

USA

run src/2.usa.ipynb

Evaluation

run src/taxonomy_evaluation.py

Train the model that classify the same occupation

  • prepare the data
  • run src/same_occupation_job_pair_sampling.py
  • run src/same_occupation_classification.py

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