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You can use the Google Patents Public Datasets (mirror), which can be accessed through Google BigQuery. For example, this query (its execution is free of charge): #legacySQL SELECT publication_number, assignee_harmonized.name, filing_date, country_code FROM [patents-public-data.patents.publications] -- WHERE UPPER(assignee_harmonized.name) LIKE 'ADOBE%' ...


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There isn't a direct way to do this through an API. What you'll want to do is develop a crawler, either local (e.g., automate IE or Selenium) or cloud-based. As Private PAIR access requires passing 2-factor authentication from the uspto.gov website, you'll need to build that authentication process into your framework. As a result, you'll need to wait for ...


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I'm not sure it does exactly what you want, but I'd recommend looking at The Lens. It can definitely display full text in the browser window and has different download options. They are working on an API so you could ask them about that. The Lens is free and non-commercial. Update: The Lens now seems to provide an API for patent data. I've not used it, but ...


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You may want to check out ANDA Litigation at https://www.amazon.com/ANDA-Litigation-Strategies-Pharmaceutical-Litigators/dp/1634254589 Yes, the book is expensive, but it's also exhaustive. It talks a lot about the requirements for patenting pharmaceutical combination drugs. As for evaluating the quality of a patent, there's two ways 1) prosecute and ...


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Here are two links to GitHub projects that can be used to help download and parse USPTO data. https://github.com/USPTO/PatentPublicData https://github.com/USPTO/bulk-data-tools I have also built a USPTO bulk data scraping and parsing software in Python3 => https://github.com/rippledj/uspto If you would like dedicated access to up-to-date USPTO data via ...


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The freepatentsonline.com expert search (www.freepatentsonline.com/search.html) is really robust free resource. Scroll down for the expert search. To do the search you've described, check the box for US Patents (and uncheck any other boxes). Then enter: AN/stanford + "machine learning" The AN stands for "assignee name" and entering "machine learning" ...


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