Using machine learning to determine electronic document similarity
US11263223B2 · kind B2 · utility
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20Claims
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Key dates
| Filing date | Oct 23, 2018 |
| Grant date | Mar 1, 2022 |
| Priority date | — |
| Expiry date | Apr 26, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/08
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods and systems for using machine learning to determine electronic document similarity include extracting entities and corresponding relationships from each of two electronic documents of a corpus of electronic documents based on word embedding, computing an entity distance between the extracted entities and a relationship distance between the extracted relationships based on knowledge graph embedding, combining the entity and relationship distances to generate a similarity score between the electronic documents, and implementing the similarity score to perform a task associated with the electronic documents.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.