UCB Fung Institute Patent Data
location: https://console.cloud.google.com/marketplace/product/google_patents_public_datasets/ucb-fung-patent
contributors: B. Balsmeier, M. Assaf, T. Chesebro, G. Fierro, K. Johnson, S. Johnson, G. Li, W.S. Lueck, D. O’Reagan, W. Yeh, G. Zang, L. Fleming
tags: patents, machine learning, disambiguation, metrics, novelty
documentation: https://funginstitute.berkeley.edu/wp-content/uploads/2016/11/Machine_learning_and_natural_language_processing_on_the_patent_corpus.pdf
timeframe: 1976-2016
terms of_use: Creative Commons Attribution 4.0 International license
description: Drawing upon recent advances in machine learning and natural language processing, we introduce new tools that automatically ingest, parse, disambiguate and build an updated database using United States patent data. The tools identify unique inventor, assignee, and location entities mentioned on each granted US patent from 1976 to 2016. We describe data flow, algorithms, user interfaces, descriptive statistics, a novelty measure based on the first appearance of a word in the patent corpus, and an automated co-inventor network mapping tool.
last edit: Fri, 01 Dec 2023 18:16:37 GMT