Hierarchical neural networks with granularized attention
US11361569B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 3, 2018 |
| Grant date | Jun 14, 2022 |
| Priority date | — |
| Expiry date | Nov 8, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG16H50/20
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Techniques are provided for generating and applying a granular attention hierarchical neural network model to classify a document. In various embodiments, data indicative of the document may be obtained (102) and processed (104) into a first layer of two or more layers of a hierarchical network model using a dual granularity attention mechanism to generate first layer output data, wherein the dual granularity attention mechanism weighs some portions of the data indicative of the document more heavily. Some portions of the data indicative of the document are integrated into the hieratical network model during training of the dual granularity attention mechanism. The first layer output data may be processed (106) in the second of two or more layers of the hierarchical network model to generate second layer output data. A classification label can be generated (108) from the second layer output data.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.