https://github.com/mkyl/chorus

Code for the paper "CHORUS: Foundation Models for Unified Data Discovery and Exploration"
https://github.com/mkyl/chorus

Last synced: 9 days ago
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Code for the paper "CHORUS: Foundation Models for Unified Data Discovery and Exploration"

• Host: GitHub
• URL: https://github.com/mkyl/chorus
• Owner: mkyl
• Created: 2024-02-28T21:49:34.000Z (11 months ago)
• Default Branch: main
• Last Pushed: 2024-04-27T21:18:06.000Z (9 months ago)
• Last Synced: 2024-04-27T22:25:01.882Z (9 months ago)
• Language: Python
• Size: 6.82 MB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Experiment code for CHORUS

This repository contains the code for the experiments in the paper "*CHORUS:

Foundation Models for Unified Data Discovery and Exploration*" to appear in VLDB 2024.

The folders are structured as follows:

- `src`: source code for the core CHORUS routines

- `experiments`: code for measuring quantitative results reported in the paper

  - `experiments/T1_table_class`: experiments for the first task, table-class detection

  - `experiments/T2_column_type`: those for the second task, column-type annotation

  - `experiments/T3_join_prediction`: those for the third task, join-column prediction

- `datasets`: benchmarks files used in this study. See `datasets/README.md` for download instructions.

- `results`: outputs of experiments as they appear in the paper

- `scripts`: code for experiments involving third-party tools

- `artifacts`: outputs of the experiments. You can download this folder at [this link](https://www.dropbox.com/scl/fi/555v71lverufsit6tidbq/chorus-artifacts.tar.xz?rlkey=jq423g2jbam88wtd5ta5glmwb&dl=0).

You can install the required packages with `pip install -r requirements.txt`. The experiments were run on Python 3.10.8.

For example, to reproduce the results of task 3 in the paper (join column prediction), run the following command:

`python experiments/T3_join_prediction/join-column-results-full.py`