Leveraging global data for enterprise data analytics
US10318864B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 24, 2015 |
| Grant date | Jun 11, 2019 |
| Priority date | — |
| Expiry date | Apr 10, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06Q10/067
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A deep learning network is trained to automatically analyze enterprise data. Raw data from one or more global data sources is received, and a specific training dataset that includes data exemplary of the enterprise data is also received. The raw data from the global data sources is used to pre-train the deep learning network to predict the results of a specific enterprise outcome scenario. The specific training dataset is then used to further train the deep learning network to predict the results of a specific enterprise outcome scenario. Alternately, the raw data from the global data sources may be automatically mined to identify semantic relationships there-within, and the identified semantic relationships may be used to pre-train the deep learning network to predict the results of a specific enterprise outcome scenario.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.