Using classified text and deep learning algorithms to identify drafting risks in a document and provide early warning
US9754206B1 · kind B1 · utility
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17Claims
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Key dates
| Filing date | Jan 23, 2017 |
| Grant date | Sep 5, 2017 |
| Priority date | — |
| Expiry date | Jan 23, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06Q10/10
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Deep learning is used to identify a potential risk that a contract will be unenforceable due to a drafting error whereby one or more terms or phrases are ambiguous. The system involves mining and using existing classifications of data (e.g., from a litigation database) to train one or more deep learning algorithms, and then examining the internal electronic drafts of contracts with the trained algorithm, to generate a scored output that will enable enterprise personnel to be alerted to the ambiguity risks and take action in time to prevent the risks from resulting in harm to the enterprise.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.