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citation Giczy, A.V., Pairolero, N.A. & Toole, A.A. Identifying artificial intelligence (AI) invention: a novel AI patent dataset. J Technol Transf 47, 476–505 (2022). https://doi.org/10.1007/s10961-021-09900-2
contributors
Alexander Giczy
Nicholas Pairolero
Andrew Toole
cost none
description The Artificial Intelligence Patent Dataset consists of two files, both released by the OCE. The first data file identifies United States (U.S.) patents issued between 1976 and 2020 and pre-grant publications (PGPubs) published through 2020 that contain one or more of several AI technology components (including machine learning, natural language processing, computer vision, speech, knowledge processing, AI hardware, evolutionary computation, and planning and control). OCE generated this data file using a machine learning (ML) approach that analyzed patent text and citations to identify AI in U.S. patent documents. The second data file contains the patent documents used to train the ML models.
documentation https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3866793
last_edit Sun, 11 Feb 2024 16:27:14 GMT
location https://www.uspto.gov/ip-policy/economic-research/research-datasets/artificial-intelligence-patent-dataset
maintained_by EconomicsData@uspto.gov
open_access TRUE
related_publications https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3866793, https://www.uspto.gov/sites/default/files/documents/OCE-DH-AI.pdf
shortname ai_patent_dataset
tags
AI
validation
patents
timeframe 1976-2020
title Artificial Intelligence Patent Dataset
uuid 335a9e17-069a-468f-b5b3-fa7151c83a8a
versioning FALSE