Natural language recommendation feedback
US10373618B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 7, 2017 |
| Grant date | Aug 6, 2019 |
| Priority date | — |
| Expiry date | Aug 7, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L2015/223
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems parse natural language expressions to extract items and values of their attributes and store them in a database. Systems also parse natural language expressions to extract values of attributes of user preferences and store them in a database. Recommendation engines use the databases to make recommendations. Parsing is of speech or text and uses conversation state, discussion context, synonym recognition, and speaker profile. Database pointers represent relative attribute values. Recommendations use machine learning to crowdsource from databases of many user preferences and to overcome the cold start problem. Parsing and recommendations use current or stored values of environmental parameters. Databases store different values of the same user preference attributes for different activities. Systems add unrecognized attributes and legal values when encountered in natural language expressions.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.