patents-public-data

(★ 686)

Patent analysis using the Google Patents Public Datasets on BigQuery

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Download Latest Version (.zip)

- - claim_text_extraction.ipynb
- BERT_For_Patents.ipynb
- Document_representation_from_BERT.ipynb
- patent_set_expansion.ipynb
- - batch_inference.py
  - batch_inference_test.py
  - generate_embedding_vocab.sql
  - hptuning_config.yaml
  - preprocess.py
  - preprocess_test.py
  - README.md
  - requirements.txt
- - __init__.py
  - AutomatedPatentLandscaping.pdf
  - AutomatedPatentLandscaping_2018Update.pdf
  - expansion.py
  - keras_metrics.py
  - LandscapeNotebook.ipynb
  - model.py
  - README.md
  - tokenizer.py
  - train_data.py
  - word2vec.py
- BERT for Patents.md
- dataset_Berkeley Fung.md
- dataset_Berkeley Fung.md.pdf
- dataset_CPA Global.md
- dataset_CPA Global.md.pdf
- dataset_European Bioinformatics Institute.md
- dataset_European Bioinformatics Institute.md.pdf
- dataset_Google Patents Public Datasets.md
- dataset_Google Patents Public Datasets.md.pdf
- dataset_Other.md
- dataset_Other.md.pdf
- dataset_USPTO.md
- dataset_USPTO.md.pdf
- index.md
- index.md.pdf
- - main.py
  - README.md
- bq_bulk_cp.pysh
- bq_ls.pysh
- csv_upload.pysh
- dataset_berkeley_fung.json
- dataset_ebi.json
- dataset_ifi.json
- dataset_innography.json
- dataset_other.json
- dataset_public.json
- dataset_report.pysh
- dataset_uspto.json
- generate_dataset_docs.py
- sqlite_dump.pysh
.gitignore
CONTRIBUTING.md
Creating a new BigQuery dataset.pdf
LICENSE
Querying a BigQuery dataset.pdf
README.md

# Installation Guide

1. Get the code

git clone https://github.com/google/patents-public-data

Downloads the entire project code from GitHub to your computer.

cd patents-public-data

Moves into the project folder you just downloaded.

2. Docker

Easy Recommended

Prerequisites

Git Needed to download the project code from GitHub.
Docker Desktop Needed to build and run containers. Install it and keep it running in the background.

⚠️ This is a large repository, so this method may point to an internal sub-package rather than the actual core product. Check the full README as well.

docker build -f tools/bigquery-indexer/beam-rdkit-runner/Dockerfile -t patents-public-data .

Builds a runnable image based on the Dockerfile.

docker run -p 8080:80 patents-public-data

Runs the built image as an actual container.

✅ Run docker compose ps to check the containers are Up. If the README mentions a port, open http://localhost:PORT in your browser.

3. Python

Easy

Prerequisites

Git Needed to download the project code from GitHub.
Python 3 On Windows, be sure to check 'Add Python to PATH' during installation.

⚠️ This is a large repository, so this method may point to an internal sub-package rather than the actual core product. Check the full README as well.

pip install -r models/claim_breadth/requirements.txt

Installs the Python libraries listed in requirements.txt (or similar).

jupyter notebook

Launches Jupyter in your browser so you can open and run the notebook (.ipynb) files.

✅ If it runs without errors and prints output in the terminal, it worked.