Normalizing electronic communications using a vector having a repeating substring as input for a neural network
US9595002B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 7, 2016 |
| Grant date | Mar 14, 2017 |
| Priority date | — |
| Expiry date | Jun 7, 2036 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/09
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Electronic communications can be normalized using a neural network. For example, a noncanonical communication that includes multiple terms can be received. The noncanonical communication can be preprocessed by (I) generating a vector including multiple characters from a term of the multiple terms; and (II) repeating a substring of the term in the vector such that a last character of the substring is positioned in a last position in the vector. The vector can be transmitted to a neural network configured to receive the vector and generate multiple probabilities based on the vector. A normalized version of the noncanonical communication can be determined using one or more of the multiple probabilities generated by the neural network. Whether the normalized version of the noncanonical communication should be outputted can also be determined using at least one of the multiple probabilities generated by the neural network.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.