Systems and methods for identifying and categorizing electronic documents through machine learning
US9514414B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 1, 2016 |
| Grant date | Dec 6, 2016 |
| Priority date | — |
| Expiry date | Apr 1, 2036 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Computer implemented systems and methods are disclosed for identifying and categorizing electronic documents through machine learning. In accordance with some embodiments, a seed set of categorized electronic documents may be used to train a document categorizer based on a machine learning algorithm. The trained document categorizer may categorize electronic documents in a large corpus of electronic documents. Performance metrics associated with performance of the trained document categorizer may be tracked, and additional seed sets of categorized electronic documents may be used to improve the performance of document categorizer by retraining the document categorizer on subsequent seed sets. Additional seed sets may and categorizations may be iterated through until a desired document categorization performance is reached.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.