Automated Patent Landscaping

location: https://github.com/google/patents-public-data/tree/master/models/landscaping

contributors: Google Patents, Aaron Abood, Dave Feltenberger

tags: machine learning, patent landscaping, citation

terms of_use: http://www.apache.org/licenses/LICENSE-2.0

documentation: https://github.com/google/patents-public-data/tree/master/models/landscaping

description: Patent landscaping is the process of finding patents related to a particular topic. It is important for companies, investors, governments, and academics seeking to gauge innovation and assess risk. However, there is no broadly recognized best approach to landscaping. Frequently, patent landscaping is a bespoke human-driven process that relies heavily on complex queries over bibliographic patent databases. This tool can be used to perform Automated Patent Landscaping, an approach that jointly leverages human domain expertise, heuristics based on patent metadata, and machine learning to generate high-quality patent landscapes with minimal effort.

last edit: Wed, 04 May 2022 11:04:06 GMT