Enterprise relevancy ranking using a neural network
US7840569B2 · kind B2 · utility
31Cited by
126References
17Claims
0Family size
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Key dates
| Filing date | Oct 18, 2007 |
| Grant date | Nov 23, 2010 |
| Priority date | — |
| Expiry date | Mar 24, 2028 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F16/951
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A neural network is used to process a set of ranking features in order to determine the relevancy ranking for a set of documents or other items. The neural network calculates a predicted relevancy score for each document and the documents can then be ordered by that score. Alternate embodiments apply a set of data transformations to the ranking features before they are input to the neural network. Training can be used to adapt both the neural network and certain of the data transformations to target environments.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.