Normalizing electronic communications using a neural-network normalizer and a neural-network flagger
US9552547B2 · kind B2 · utility
Assignees
Inventors
Key dates
| Filing date | Nov 10, 2015 |
| Grant date | Jan 24, 2017 |
| Priority date | — |
| Expiry date | Nov 10, 2035 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L51/063
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Electronic communications can be normalized using neural networks. For example, an electronic representation of a noncanonical communication can be received. A normalized version of the noncanonical communication can be determined using a normalizer including a neural network. The neural network can receive a single vector at an input layer of the neural network and transform an output of a hidden layer of the neural network into multiple values that sum to a total value of one. Each value of the multiple values can be a number between zero and one and represent a probability of a particular character being in a particular position in the normalized version of the noncanonical communication. The neural network can determine the normalized version of the noncanonical communication based on the multiple values. Whether the normalized version should be output can be determined based on a result from a flagger including another neural network.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.